1. Assessing Bank Erosion Potential in the San Antonio River
Jose Silvestre
J.K Haschenburger

2. Background
Cohesive
Mass wasting
Non-cohesive
Fluvial erosion

3. Study Objectives 2. Predict streambank erosion rates
3. Determine dominant type of erosional process occurring
Aid in River Management
1. Assess potential for erosion

4. Study Area
Study reach in lower portion of watershed (downstream of City of San Antonio)
Meandering river where the bed is dominated by sand-sized sediment
Bank sediment characteristics are known to differ along the lower reach
A = Floresville
B = Goliad

5. Bank Erosion Hazard Index (BEHI)
BANCS Model
Evaluates bank characteristics and flow distribution along river reaches
Bank Erosion Hazard Index (BEHI)
Annual Erosion Rates
Near Bank Stress (NBS)
Rosgen (2001b, 2006b)

6. BANCS Model: BEHI
Root Density
Bankfull

7. BANCS Model: BEHI Bank Height/ Bankfull Height
Convert Values to BEHI Scores
Adjust Scores for Bank Materials
Adjust Scores for Stratification
Obtain Total Score and Adjective BEHI Rating
Root Depth/Bank Height
Weigted Root Density
Bank Angle
Surface Protection

8. Measurements for BEHI Root Depth 3 partitions along the vertical
3 vertical partitions where multiple measurements were taken

9. Measurements for BEHI Root Density 3 partitions along the vertical
3 vertical partitions where multiple measurements were taken

10. Measurements for BEHI Surface Protection
Bank Angle
Top of Bank
Bank Height
3 partitions along the horizontal where multiple measurements were taken

11. BANCS Model: NBS

12. Measurements for NBS ÷ = Wetted width divided into 10 partitions
Max depth measured for partition nearest study bank
Near-bank max depth
Depth measured for each partition
Depth measurements averaged
Convert to rating ÷ =
Mean Depth
NBS

13. Near Bank Stress Rating
Potential for Erosion
Site
Bank ID
BEHI Score
Erosion Potential
NBS Score
Near Bank Stress Rating
Floresville-U
BK06
42.6
Very High
1.59
Moderate
Floresville-M
BK01
27.6
0.75
Very Low
Floresville-L
BK03
37.2
High
1.53
Goliad-U
BK02
33.1
1.72
Goliad-M
BK04
43.1
1.99
Goliad-L
BK05
35.8
1.57
BEHI scores range from or moderate to very high erosion potential

14. Near Bank Stress Rating
Potential for Erosion
Site
Bank ID
BEHI Score
Erosion Potential
NBS Score
Near Bank Stress Rating
Floresville-U
BK06
42.6
Very High
1.59
Moderate
Floresville-M
BK01
27.6
0.75
Very Low
Floresville-L
BK03
37.2
High
1.53
Goliad-U
BK02
33.1
1.72
Goliad-M
BK04
43.1
1.99
Goliad-L
BK05
35.8
1.57
NBS scores range from or very low to high

15. Erosion Rates Developed for streams found in sedimentary geology
BEHI Rating
Rating Curve
Low
BER = e0.7349(NBS)
Moderate
BER = e0.5057(NBS)
High/Very High
BER = 0.109e0.4159(NBS)
Extreme
BER = e0.9391(NBS)
Rosgen 1996, 2001b, 2006b
Developed for streams found in sedimentary geology

16. Erosion Rates BEHI Rating Rating Curve Low BER = 0.0082e0.7349(NBS)
Moderate
BER = e0.5057(NBS)
High/Very High
BER = 0.109e0.4159(NBS)
Extreme
BER = e0.9391(NBS)
Rosgen 1996, 2001b, 2006b
Bank Erosion Rate

17. Erosion Rates BEHI Rating Rating Curve Low BER = 0.0082e0.7349(NBS)
Moderate
BER = e0.5057(NBS)
High/Very High
BER = 0.109e0.4159(NBS)
Extreme
BER = e0.9391(NBS)
Rosgen 1996, 2001b, 2006b
Bank Erosion Rate
Near Bank Stress

18. Erosion Rates BEHI Rating Rating Curve Low BER = 0.0082e0.7349(NBS)
Moderate
BER = e0.5057(NBS)
High/Very High
BER = 0.109e0.4159(NBS)
Extreme
BER = e0.9391(NBS)
Rosgen 1996, 2001b, 2006b
Bank Erosion Rate
Empirically derived constants
Near Bank Stress

19. Erosion Rate tons/m/yr.
Erosion Rates
Bank ID
Erosion Rate tons/m/yr.
Ghosh et al. (2006) - India
0.83
Rosgen (2001b) – Yellowstone
0.23
Rosgen (2001b) – Colorado
0.18
Hickey Run – Washington, D.C
0.17
San Antonio River
0.16
Predicted Erosion Rate
(m/yr.)
Length of Bank
(m)
Bank Height.
(m) x x
Multiply by 1.7 to get tons/yr.
Divide by length of channel to get tons/m/yr.

20. Sediment Analysis

21. Sediment Analysis Non-slumped areas (BK01 & BK02)
Coarser sediment in middle and upper partitions indicate higher flows influence grain sizes present

22. Concluding Remarks
Banks have high erosion potential based on the mean BEHI metric.
Moderate NBS values support mass wasting as dominant erosional process
Based on obtained data, erosion rate per unit length of channel is low in comparison to rates from other studies
Particle size distributions in non-slumped areas suggest coarse material is found in upper partition of banks, which suggests that higher magnitude flows influence the grain sizes present.

23. Future Work
Incorporate the frequency and magnitude of flood events to gain a better understanding of annual erosion potential.
This understanding will help create a model that better describes the bank erosional processes that occur along the San Antonio River.

24. Acknowledgements
Many thanks to Nick Castillo for his contributions to this project. Funding was provided by the Minority Education in Earth Science and Environmental Engineering (MORESE) Program through the University of Texas at San Antonio and the San Antonio River Authority.

25. References
Haschenburger, J.K., Curran. J., Sediment Transport Modeling of Reach Scale Geomorphic Processes. TWDB Contract No
Julian, J.P., Torres, R., Hydraulic erosion of cohesive riverbanks. Geomorphology 76,
Rosgen. D.L. 2006, Watershed assessment of river stability and sediment supply (WARSSS), Wildland Hydrology, Fort Collins, Colorado
Kwan, Hilda and Sherman Swanson, Prediction of Annual Streambank Erosion for Sequoia National Forest, California. Journal of the American Water Resources Association (JAWRA) 50(6)
Shields, I.A., Application of similarity principles and turbulence research to bedload movement. In: Ott, W.P., can Uchelen, J.C. (Eds.), (Translators), Hydrodynamics Laboratory Publication vol California Institute of Technology, Pasadena
Thorne, C.R., Processes and mechanisms of river bank erosion. In Hey, R.D. Thorne, C.R., Bathurst, J.C. (Eds), Gravel-bed Rivers. Wiley and Sons, Chichester, UK, pp

26. Questions?