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

Background Cohesive Mass wasting Non-cohesive Fluvial erosion

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

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

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)

BANCS Model: BEHI Root Density Bankfull

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

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

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

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

BANCS Model: NBS

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

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 27.6-43.1 or moderate to very high erosion potential

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 0.75-1.99 or very low to high

Erosion Rates Developed for streams found in sedimentary geology BEHI Rating Rating Curve Low BER = 0.0082e0.7349(NBS) Moderate BER = 0.0556e0.5057(NBS) High/Very High BER = 0.109e0.4159(NBS) Extreme BER = 0.0642e0.9391(NBS) Rosgen 1996, 2001b, 2006b Developed for streams found in sedimentary geology

Erosion Rates BEHI Rating Rating Curve Low BER = 0.0082e0.7349(NBS) Moderate BER = 0.0556e0.5057(NBS) High/Very High BER = 0.109e0.4159(NBS) Extreme BER = 0.0642e0.9391(NBS) Rosgen 1996, 2001b, 2006b Bank Erosion Rate

Erosion Rates BEHI Rating Rating Curve Low BER = 0.0082e0.7349(NBS) Moderate BER = 0.0556e0.5057(NBS) High/Very High BER = 0.109e0.4159(NBS) Extreme BER = 0.0642e0.9391(NBS) Rosgen 1996, 2001b, 2006b Bank Erosion Rate Near Bank Stress

Erosion Rates BEHI Rating Rating Curve Low BER = 0.0082e0.7349(NBS) Moderate BER = 0.0556e0.5057(NBS) High/Very High BER = 0.109e0.4159(NBS) Extreme BER = 0.0642e0.9391(NBS) Rosgen 1996, 2001b, 2006b Bank Erosion Rate Empirically derived constants Near Bank Stress

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.

Sediment Analysis

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

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.

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.

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.

References Haschenburger, J.K., Curran. J., 2012. Sediment Transport Modeling of Reach Scale Geomorphic Processes. TWDB Contract No. 0904830899 Julian, J.P., Torres, R., 2006. Hydraulic erosion of cohesive riverbanks. Geomorphology 76, 193-206 Rosgen. D.L. 2006, Watershed assessment of river stability and sediment supply (WARSSS), Wildland Hydrology, Fort Collins, Colorado Kwan, Hilda and Sherman Swanson, 2014. Prediction of Annual Streambank Erosion for Sequoia National Forest, California. Journal of the American Water Resources Association (JAWRA) 50(6) Shields, I.A., 1936. Application of similarity principles and turbulence research to bedload movement. In: Ott, W.P., can Uchelen, J.C. (Eds.), (Translators), Hydrodynamics Laboratory Publication vol. 167. California Institute of Technology, Pasadena Thorne, C.R., 1982. 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. 227-259

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