Mapping Watershed-scale Streambank Erosion Using EPA- BANCS for Determining TMDLs
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1 Mapping Watershed-scale Streambank Erosion Using EPA- BANCS for Determining TMDLs Paul Ayers, K. Hensley, D. Wade Biosystems Engineering & Soil Science University of Tennessee K. Swinson (Geosyntec), B. Connell (Trutta) University of Tennessee Alum
2 Sediment in Streams Where does the sediment come from upland erosion? in stream erosion? How much sediment comes from these sources? Some sediment TMDLs ignore streambank erosion
3 Research Objectives To develop and demonstrate a rapid watershed-scale data collection method to predict total daily sediment load (TDSL) and total maximum daily load (TMDL) for streambank erosion Implement Streambank Video Mapping System (SVMS) Map streambank condition Utilize Bank Assessment for Non-point source Consequences of Sediment (EPA BANCS) method Evaluate erodibility and erosivity Predict Bank Erosion Rate (BER) Utilize flow data Predict TDSLs and develop TMDLs
4 Driftwood River Assessment Located in Indiana, adjacent to Camp Atterbury Funded by Department of Defense Legacy Program (through Army COE CERL) Look at stream bank erodibility 12 mile section mapped Flow
5
6 WATERPROOF CASE SONAR TRANSDUCER LASERS VIDEO CAMERAS
7 Streambank Video Mapping System (SVMS) GPS Position Depth Width Video streambank condition
8 Mapping In Progress
9 EPA - Watershed Assessment of River Stability & Sediment Supply (WARSSS) Bank Assessment for Non-point source Consequences of Sediment (BANCS) model BANCS predicts annual streambank rescission (in/yr) at a sample location (Bank Erosion Rate) BER = f (BEHI, NBS) BEHI Bank Erosion Hazard Index NBS- Near-Bank Stress = f(rc/w, etc) Estimate site-specific annual and total daily streambank erosion (tons/feet of streambank) Determine areas of high streambank erosion rates TMDL determinations
10 SVMS Ocular Assessment BEHI* (erodibility) Rc/W NBS (erosivity) Implementing EPA BANCS Method BER USGS flow data TDSL
11 SVMS Ocular Assessment BEHI* (erodibility) Rc/W NBS (erosivity) Implementing EPA BANCS Method BER USGS flow data TDSL
12
13 Modified Bank Erosion Hazard Rating Modified Bank Erosion Hazard Index (BEHI*) BankHeight to Bankfull Height (Ratio) Riparian Diversity x 2 (%) Bank Angle (Degrees) Low Value Optimal Index Moderate Value Sub Opt Index High Value Marginal Index Very Extreme High Value > 2.1 Poor > 91 < 14 Index Based on Connell, 2012 Surface Protection ( %) Index Totals
14 BEHI* Score = Rating = Very High Bank Angle = 6.95, BH/BF Ratio = 6.95, Surface Protection = 18, Riparian Diversity = 6.95 Bank Angle (deg) Bank Height (ft) 0-60 = = =6.95 > 91 =9 0-1ft 1ft-3ft 3ft - 6ft 6ft-9ft 9ft-12ft 12ft-18ft Surface Protection (Avg. %) = = =6.95 < 14 =9 Riparian Diversity Optimal =4.9 Sub Opt =9.9 Marginal =13.9 Poor =18 14:39 14:39 14:39 14:39
15 BEHI* Total Low Moderate High Very High Georeferenced Data in ArcGIS
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17
18 SVMS Ocular Assessment BEHI* (erodibility) Rc/W NBS (erosivity) Implementing EPA BANCS Method BER USGS flow data TDSL
19 Near Bank Stress (NBS) Determining NBS from Rc/W: Rc = Radius of curvature W = River width NBS Categories very low to extreme Values 1 to 6 NBS Description NBS Value Rc/W Very Low 1 > 3.0 Low Moderate High Very High Extreme 6 < 1.5 WARSS,
20 Stream Erosivity (R C /W)
21 SVMS Ocular Assessment BEHI* (erodibility) Rc/W NBS (erosivity) Implementing EPA BANCS Method BER USGS gage data TDSL
22 North Carolina Piedmont Region Bank Erosion Prediction Curve
23
24
25 Ocular Assessment BEHI* (erodibility) SVMS Rc/W NBS (erosivity) Predicting Total Daily Sediment Load (TDSL) BER USGS flow data TDSL
26 USGS Gage Station
27 Flow Rate (cfs) Average Daily Flow (cfs) for Driftwood River ( ) Julian Day
28 Estimating: USGS Stream Gage Data Lateral Erosion Rate = f(q 0.6 ) Q = flow rate Based on a power factor (Evans et al., 2003) Erosion Potential LER i / i LER Julian Day Month Number Day Number Begin Yr End Yr Mean Flow LER Erosion Potential % Erosion Potential
29 % Daily Flow Erosion Potential 0.6 Flow Erosion Potential vs. Flow Rate Flow Rate (cfs)
30 SVMS Predicting Total Daily Ocular Assessment Rc/W Sediment Load BEHI* (erodibility) BER NBS (erosivity) (TDSL) From site-specific BER and erosion potential based on USGS flow data USGS flow data TDSL
31 Predicting TDSL Estimating Sediment Loads: Site-specific daily erosion rate (DER) BER (ft/yr) x % erosion potential Site-specific daily sediment load (DSL) DER x bank height x bank length x soil density Total daily sediment load (TDSL) Site-specific DSL
32
33 Flow Rate (cfs) 1800 Storm Event on the Driftwood River May 31-May 1-Jun 2-Jun 3-Jun 4-Jun 5-Jun 6-Jun 7-Jun 8-Jun 9-Jun Day Flow
34 Flow Rate (cfs) TDSL (tons/day) Storm Event on the Driftwood River May 31-May 1-Jun 2-Jun 3-Jun 4-Jun 5-Jun 6-Jun 7-Jun 8-Jun 9-Jun Day Flow TDSL
35 Streambank Ocular Assessment BEHI* (erodibility) SVMS BER Bank erosion rate Rc/W NBS (erosivity) Developing Sediment Total Maximum Daily Load (TMDL) using EPA BANCS USGS flow data TDSL Total daily sediment load TMDL For Sediment
36 Developing TMDLs Using Equation Long Term Average (LTA) = µ Mean TDSL over a desired time period Coefficient of variation (CV) = standard deviation µ (mean) σ 2 = ln(cv 2 +1) Recurring interval: 365 days, z score = Maximum Daily Load (MDL) = LTA * e (zσ 0.5σ^2) An approach for using load duration curves in developing TMDLs (EPA, 2006)
37 Developing TMDLs Driftwood River Long Term Average = 13 tons/day Approximately 980 cfs SDev= 5.57 tons/day CV = mi Reach MDL 70 tons/day MDL flow rate Approximately 15,200cfs Occurs <1% of the time over a 49yr period
38 Driftwood River Peak Flow Rate
39 Benefits of Streambank Video Mapping Integrate with the EPA BANCS method Predict erodibility and erosivity Estimate total annual or daily streambank erosion Develop TMDL utilizing EPA protocol Evaluate restoration impacts Cover large areas (10 miles/day) - continuous Non-intrusive, no access required Permanent historical video database The advantage of video mapping every foot of stream and bank is that 1) the total daily streambank erosion can be determined, and 2) the locations of high erosion can be identified and managed
40 Questions? Contact: Paul Ayers Biosystems Engineering University of Tennessee
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