HomeMy WebLinkAboutFINAL REPORT Hydraulic and potential sediment transport impacts of hydrokinetic energy extraction at Tanana site near Nenana Alaska 6 SEPT 20141
Hydraulic and potential sediment transport impacts of hydrokinetic energy extraction from
the Tanana River near Nenana, Alaska
Sept. 6, 2014
Tom Ravens and Maria Kartezhnikova
College of Engineering
University of Alaska Anchorage
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Abstract
In this portion of the statewide hydrokinetic feasibility study, UAA addressed the issue of hydraulic and
sediment transport impacts of hydrokinetic (HK) devices on the Tanana River by Nenana. Hydraulic and
sediment transport models were created for Tanana site using SNL-EFDC software developed by Sandia
Lab and Environmental Protection Agency (EPA). The hydraulic model was verified using velocity
measurements collected at the study site. The hydraulic model was modified to represent the presence
of HK devices using two different approaches. The two methods were in good agreement, and they
demonstrated that hydrokinetic energy extraction causes water level rise upstream of the area of HK
device deployment with negligible water level effects downstream of the device. Velocity downstream
of the HK device is reduced (in its wake) due to energy extraction, and it is increased outside of the
wake. Also, both approaches demonstrated that the hydraulic effects of relatively few devices in
medium to large rivers (e.g., Tanana River) are relatively small. These findings are described in detail in
thesis by Kartezhnikova (2013).
The sediment transport model was developed based on the hydraulic model described above and in
Kartezhnikova (2013). The sediment transport model for the site could not be fully validated due to the
limited data available. Nonetheless, bedload generated by the sediment transport model was in general
agreement with estimates based on sediment rating curve equations derived by Toniolo (2013). We
recommend that bottom sediment, suspended load, and bedload data be collected for the site in order
to calibrate and improve the sediment transport models. Consistent with the velocity change patterns
due to hydrokinetic energy extraction, sediment transport models indicated a deposition area
downstream of the device and areas of erosion outside of the wake area where velocity had been
enhanced by the presence of the device. Sediment bed change rates are within +/- 1, +/- 2, and +/- 2.5
cm/day (for RivGen device) at 1250, 1750, and 2250 m3/s modeled flow rates.
Using the calculated rates of sediment bed change and ten years of flow rate data during the open-
water season at the Tanana site, the overall open-water season bed variation due to HK device
operation was estimated and rounded up to +/-2 m.
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Table of Contents
Abstract ......................................................................................................................................................... 2
Table of Contents .......................................................................................................................................... 3
List of Figures ................................................................................................................................................ 4
List of Tables ................................................................................................................................................. 4
1 Hydraulic impacts of hydrokinetic energy extraction at Tanana site ................................................... 5
2 Potential sediment transport impacts of hydrokinetic energy extraction at Tanana site .................... 5
2.1 Seven days sediment transport model for Tanana site ................................................................ 6
2.2 Potential impacts of hydrokinetic energy extraction on sediment transport at different flow
rates….. ................................................................................................................................................... 10
2.3 Potential impacts of hydrokinetic energy extraction within open-water season ...................... 17
3 Conclusion and recommendation ....................................................................................................... 18
Appendix: Open-water season discharge data analysis ............................................................................. 20
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List of Figures
Figure 1: Sediment class sizes and sediment transport parameters in EFDC Explorer. ............................... 6
Figure 2: Selected EFDC computational options for sediment transport modeling. .................................... 7
Figure 3: Sediment bed layer depth average d50 (mm) distribution as the result of one week (7 days)
sediment transport model run at a constant discharge of 1750 m3/s. ........................................................ 8
Figure 4: Sediment bed changes (m) due to one week (7 days) sediment transport model run at a
constant discharge of 1750 m3/s. ................................................................................................................. 9
Figure 5: Froude number (Fr) values at constant discharge of 1750 m3/s. .................................................. 9
Figure 6: Changes in depth (cm) due to hydrokinetic energy extraction at 2250 m3/s. ............................ 11
Figure 7: Changes in velocity (cm/s) due to hydrokinetic energy extraction at 2250 m3/s. ...................... 12
Figure 8: Changes in sediment bed (cm/day) due to hydrokinetic energy extraction at 2250 m3/s.......... 12
Figure 9: Changes in depth (cm) due to hydrokinetic energy extraction at 1750 m3/s. ............................ 13
Figure 10: Changes in velocity (cm/s) due to hydrokinetic energy extraction at 1750 m3/s. .................... 14
Figure 11: Changes in bed (cm/day) due to hydrokinetic energy extraction at 1750 m3/s........................ 14
Figure 12: Changes in depth (cm) due to hydrokinetic energy extraction at 1250 m3/s. .......................... 15
Figure 13: Changes in velocity (cm/s) due to hydrokinetic energy extraction at 1250 m3/s. .................... 16
Figure 14: Changes in bed (cm/day) due to hydrokinetic energy extraction at 1250 m3/s........................ 16
Figure 15: Frequency of Tanana river discharge occurrence during the open-water season (May-October)
based on ten years records (2003-2014) on Tanana River, near Nenana, Alaska. ..................................... 20
List of Tables
Table 1: Impact of hydrokinetic energy extraction .................................................................................... 17
Table 2: Statistical analysis of flow categories of the open-water season (May-October) based on ten
years records (2003-2014) on Tanana River, near Nenana, Alaska. ........................................................... 21
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1 Hydraulic impacts of hydrokinetic energy extraction at Tanana site
A three-dimensional hydraulic model for the Tanana site was created with Sandia National Laboratories
Environmental Fluid Dynamics Code (SNL-EFDC). The hydraulic model was verified and evaluated. SNL-
EFDC results agreed quite well with the measured data. Average transect velocity error was only 3.52%
with point velocity measurements along transects averaging 14.81%. Using the capabilities of SNL-EFDC,
effects of hydrokinetic (HK) energy extraction were determined. Results for Tanana site indicated that
the deployment of RivGen (manufactured by Ocean Renewable Power Corporation) downstream of the
bridge may cause a water level rise of 3 mm upstream from area of deployment at the modeled
discharge (Q = 1,789.63 m3/s). The velocity downstream of the device (i.e., in its wake) decreased by
0.05 m/s and velocity outside of the wake zone would increase by 0.02 m/s, according to model
calculations. These changes in velocity indicate potential areas of sedimentation (in the wake) and
erosion (outside of the wake). Changes in velocities are significantly reduced 100m downstream of
RivGen and they become negligible at a distance of 350m. It was also determined that the support
structure contributed almost 50% to the hydraulic impacts due to RivGen deployment. Optimization of
the support structure design may help reduce hydraulic impacts.
Details regarding software modeling technics, data used for model creation, HK device representation in
a model, model error analysis, and detailed data on hydraulic effects of HK devices can be found in
thesis “Hydraulic impacts of hydrokinetic energy extraction in rivers” (Kartehnikova, 2013).
2 Potential sediment transport impacts of hydrokinetic energy extraction at Tanana site
The sediment transport model for the site was created based on the verified flow model described
above. However, due to time constraints, the hydraulic model was run in 2D mode. Due to the limited
sediment data, a spatially uniform distribution of the sediments was assumed, for initial calculations. In
this initial model, it was also assumed that the active sediment bed was 1.5 m thick, and it included
three distinct sediment sizes: 0.25mm, 16 mm, and 50mm. To generate a realistic spatial distribution of
grain size, the model was run for 7 days at a flow of 1750 m3/s which is the 80 percentile flow for the
river during open water conditions. The calculated bed conditions from the seven-days simulation run
was then used as initial sediment bed conditions for hydrokinetic energy extraction model simulations.
HK sediment transport models were created for 1250, 1750, and 2250 m3/s flow rates based on open-
water season discharge data analysis (see Appendix A). Discharge of 750 m3/s was originally included in
analysis; however RivGen device is a self-starting cross-flow turbine at velocity of 2 knots (1 m/s).
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Velocity at the area of device deployment is approximately 1 m/s at 750 m3/s flow rate and whether or
not device will be operating at given discharge is not clear. Also, changes in bed layer at 1250 m3/s flow
rate were quite small, and changes in bed at lower flow rates were assumed to be insignificant.
Each HK sediment model was run for one day to establish erosion and sedimentation rates due to
hydrokinetic energy extraction. Model results were used to investigate and evaluate potential impacts
of HK device on Tanana site during open-water season period.
2.1 Seven days sediment transport model for Tanana site
Uniform sediment bed characteristics were approximated using data from TerraSond report (TerraSond,
2011) and “Bed Forms and Sediment Characteristics along the Thalweg on the Tanana River near
Nenana, Alaska, USA “ publication (Toniolo, 2013). One sediment layer (1.5 meters thick) and three
discrete sediment sizes (0.25mm, 16 mm, and 50mm) were chosen for the modeling effort to represent
the distribution of surface bed sediments. The number of sediment classes was set following
recommendation of optimal number of sizes for the sediment transport routines in the EFDC code
(James et al., 2006). Below is the summery of sediment class sizes and defined sediment transport
parameters in EFDC Explorer.
Figure 1: Sediment class sizes and sediment transport parameters in EFDC Explorer.
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The fraction of each sediment class in the sediment bed was determined empirically. Initially, it was
assumed that the three particle sizes were equally represented in the sediment bed. However,
calculated bed changes (after running for 7 days) were more reasonable if we assumed the following
bed composition: 20% of the fine sediments, 40% of the middle-sized sediments, and 40% of the large-
sized sediments.
The “Aggregate Bed Shear” option was chosen for the bed shear computations (Figure 2), which is a
method to compute the bed shear based on the hydrodynamic conditions over the bed. The timestep
for sediment transport was set to 3, which is greater than hydraulic timestep, in order to provided
adequate computational time and avoid instability issues (Figure 2). Non-cohesive armoring function
was activated and settling flag was set to zero (“Simple”) for sediments (Figure 1). Bedload function was
activated as well (Figure 2) and Van Rijn approach was selected for computing sediment concentration
near the bed (equilibrium layer) during the model run (Figure 1). Constant porosity of 0.4 was used
throughout the entire model domain.
Figure 2: Selected EFDC computational options for sediment transport modeling.
Discharge of 1750 m3/s was used for the seven-day simulation model. Toniolo (2013) provides sediment
rating curves based on point measurements of bedload and suspended load. For a 1750 m3/s discharge,
Toniolo’s point bedload measurements with a Helley-Smith sampler suggest a point bedload transport
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of about 12.8 g/s. His rating curves suggest a suspended sediments concentration (SSC) of 1922.3 mg/s.
Model generated BL was between 0 mg/s and 18 g/s in active cells. This was considered very low since
the computation grid cells were much larger than the size of the Helley-Smith sampler. SSC was
significantly less than of those predicted by rating curve formula. This is probably because only non-
cohesive sediment transport was modeled. Model generated SSC is between 0 mg/L and 300 mg/L. Due
to the lack of sediment transport data measurements and/or change in bed measurements, model could
not be verified any further. Nonetheless, one-week sediment transport model produces quite realistic
redistribution of bed layer sediments, with finer d50 of bed layer on the side of the river channel and
river bend, and with coarser sediments at high velocity zones (Figure 3). Overall, bed layer fluctuations
are within +/-0.5 meters for one week run (Figure 4). Model also indicates migration of river dunes in
the direction of the flow, which is in agreement with characteristic of subcritical flow (Fr <1, Figure 5).
Figure 3: Sediment bed layer depth average d50 (mm) distribution as the result of one week (7 days)
sediment transport model run at a constant discharge of 1750 m3/s.
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Figure 4: Sediment bed changes (m) due to one week (7 days) sediment transport model run at a
constant discharge of 1750 m3/s.
Figure 5: Froude number (Fr) values at constant discharge of 1750 m3/s.
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2.2 Potential impacts of hydrokinetic energy extraction on sediment transport at different flow rates
Overall, six SNL- EFDC models were created for analysis of HK impacts. Three models with HK devices
were run using SNL-EFDC ability for three different flow rates, 1250, 1750, and 2250 m3/s. And three
models at the same flow rates were run without HK devices. Velocity, water level, and sediment bed
outputs were extracted from models with HK devices and compared to those from the Tanana models
without hydrokinetic energy extraction.
Note: The inlet/outlet boundary and water-land boundary are typically the more unstable and sensitive
areas in modeling routines. Due to this sensitivity, model sometime generates unrealistic results
(“spikes”) right on boundaries. These “spikes” or jumps in model outputs right at the boundaries (water-
land boundary or inlet/outlet boundary) are visible in some of the Figures 6-14 due to interpolation
routines used. It should be understood that those jumps in data are not representative and should be
considered as noise in a model.
Figures 6, 7 and 8 demonstrate changes in the water depth, velocity, and sediment bed due to
hydrokinetic energy extraction as determined by the SNL-EFDC approach at 2250 m3/s flow rate.
Placement of HK device causes the water level to rise upstream of the deployment area by 0.4 cm, with
negligible effects downstream of the HK device (Figure 6). There was some noteworthy cross-channel
variation in water depth (+/- 0.5 cm) near the deployment area.
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Figure 6: Changes in depth (cm) due to hydrokinetic energy extraction at 2250 m3/s.
Figure 7 demonstrates that hydrokinetic energy extraction causes velocity reduction of about 6 cm/s in
the wake of (downstream of) the device and enhanced velocity by 2-3 cm/s outside the wake of the
devices.
One day model run resulted in sediment bed fluctuation of +/-2.5 cm due to the HK device operation
(Figure 8). Following velocity change patterns, sediment transport model indicated deposition area
downstream of the device (up to 2.5 cm) and distinctive area of erosion downstream and to the left of
the device, facing in the flow direction (-2.5 cm). There are some depositional patterns on the left side
river bank downstream of the device and slight erosion on the right side bank in the proximity of the
device location.
The average power output by the HK device (RivGen) was reported at 32.6 kW at the modeled flow rate
of 2250 m3/s.
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Figure 7: Changes in velocity (cm/s) due to hydrokinetic energy extraction at 2250 m3/s.
Figure 8: Changes in sediment bed (cm/day) due to hydrokinetic energy extraction at 2250 m3/s.
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Figures 9, 10 and 11 demonstrate changes in the water depth, velocity, and sediment bed due to
hydrokinetic energy extraction as determined by the SNL-EFDC approach at 1750 m3/s flow rate.
Patterns of changes in water depth and velocity are similar to those described in the previous model.
The extent of changes is slightly less due to the lower velocities and consequently lower power output
by HK device. Water level rise upstream of the deployment area is about 0.3 cm (Figure 9) and velocity
changes due HK energy extraction are within +/-5 cm/s (Figure 10).
One day model run resulted in sediment bed fluctuation of +/-2 cm due to the HK device operation
(Figure 11). Similar to model with higher flow rate, there are a deposition area downstream of the
device (up to 2 cm) and erosion area downstream and to the left of the device (-2 cm). However, due to
the lower velocities, these areas are smaller and more defined.
The average power output by the HK device (RivGen) was reported at 21.2 kW at the modeled flow rate
of 1750 m3/s.
Figure 9: Changes in depth (cm) due to hydrokinetic energy extraction at 1750 m3/s.
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Figure 10: Changes in velocity (cm/s) due to hydrokinetic energy extraction at 1750 m3/s.
Figure 11: Changes in bed (cm/day) due to hydrokinetic energy extraction at 1750 m3/s.
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The last model was created at 1250 m3/s discharge. Patterns of changes in water depth and velocity due
to hydrokinetic energy extraction are similar to those described in the previous models and
demonstrated in Figures 12 and 13. Water level rise upstream of the deployment area is about 0.2 cm
(Figure 12) and velocity changes due HK energy extraction are within +/-2.5 cm/s (Figure 13).
One day model run resulted in sediment bed fluctuation of +/-1 cm due to the HK device operation
(Figure 14). There is a small deposition area downstream of the device (up to 1 cm) and erosion area
downstream to the left of the device (-1 cm).
The average power output by the HK device (RivGen) was reported at 9.9 kW at the modeled flow rate
of 1250 m3/s.
Figure 12: Changes in depth (cm) due to hydrokinetic energy extraction at 1250 m3/s.
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Figure 13: Changes in velocity (cm/s) due to hydrokinetic energy extraction at 1250 m3/s.
Figure 14: Changes in bed (cm/day) due to hydrokinetic energy extraction at 1250 m3/s.
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2.3 Potential impacts of hydrokinetic energy extraction within open-water season
Using determined frequency of each discharge group (see Appendix, Table 2) and rates of sediment bed
change determined by modeling, the overall open-water season (153 days long) bed variation due to HK
device operation can be approximated (Table 1). Overall impacts on the river bed sum ups to +/-1.7 m
(Table 1). This result is conservatively rounded up to +/-2 m, since even if HK device may not be
operating at 750 m3/s flow rate (due to the low velocity), it will still impact sediment transport due to
the drag force exerted on support structure of the HK device.
Table 1: Summery of impacts of hydrokinetic energy extraction at Tanana site.
Flow groups (m3/s)
Parameters units <1000 1000-1500 1500-2000 >2000
Modeled discharge m3/s 750 1250 1750 2250
Water level changes cm negligible +/- 0.2 +/- 0.3 +/- 0.5
Velocity changes cm/s negligible +/- 2.5 +/- 5 +/- 6
Sediment bed change rate cm/day negligible +/- 1 +/- 2 +/- 2.5
Frequency % 26 38 32 4
Frequency per open-water season days 39.8 58.1 49.0 6.1
Sediment bed change per open-
water season cm negligible +/- 58.1 +/- 97.9 +/- 15.3
Total sediment bed variation per open-water season: +/- 171.3 cm
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3 Conclusion and recommendation
Hydraulic and sediment transport models were developed for Tanana site to investigate impacts of
hydrokinetic energy extraction using SNL-EFDC. Hydraulic model was verified using velocity
measurements with average transect velocity error of only 3.5%. Meanwhile, sediment transport
models for the site could not be fully verified due to the limitations in available data. Nonetheless,
bedload generated by models were in somewhat agreement with estimations based on sediment rating
curves equations derived by Toniolo (2013). Suspended sediment concentrations were significantly
lower of predicted values since only non-cohesive sediment transport were modeled. One week
sediment transport model simulation produce +/-0.5 m fluctuation of sediment bed.
Hydrokinetic energy extraction models for the site indicated water level rise upstream of hydrokinetic
device of the magnitude 0.2, 0.3, and 0.5 cm at 1250, 1750, and 2250 m3/s flow rates, with negligible
water level changes downstream of the device. Hydrokinetic energy extraction causes velocity reduction
at the area of deployment and downstream of the devices with enhanced velocity around the wake of
the device. Changes in velocity are within +/- 2.5, +/- 5, and +/- 6 cm/s at 1250, 1750, and 2250 m3/s
flow rates respectively. Following velocity change patterns, sediment transport models indicated
deposition area downstream of the device and areas of erosion around wake of the device. Models
indicated distinctive area of erosion downstream and to the left of the device. Sediment bed change
rates are within +/- 1, +/- 2, and +/- 2.5 cm/day at 1250, 1750, and 2250 m3/s flow rates. Using
determined rates of sediment bed change and analysis of ten year records of flow rates during the open-
water season at Tanana site, the overall open-water season bed variation (following determined
erosion/sedimentation patterns) due to HK device operation is estimated as +/-1.7 m. This result is
conservatively rounded up to +/-2 m of sediment bed fluctuation per open-water season as the result of
hydrokinetic energy extraction at Tanana site.
It is recommended to collect sediment and bedload data for the site in order to be able to improve and
calibrate sediment transport models. It is also recommended to use SEDZLJ sediment transport model
developed by Ziegler, Lick, and Jones (James et al. 2010), instead of regular sediment transport routines
provided by SNL-EFDC. SEDZLJ’s ability to provide unified treatment of both cohesive and non-cohesive
particle transport ensures more accurate representation of erosion processes.
It is also recommended to collect more bathometric and velocity data upstream, so that model can be
extended, and other HK device locations can be investigated.
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References
James, S.C., Parmeshwar, L.S., and Jesse, D.R. (2006). Modeling Noncohesive Sediment Transport Using
Multiple Sediment Size Classes. In: Journal of Coastal Research Vol. 22, No. 5 (Sep., 2006). pp. 1125-
1132.
James, S.C., Craig, J., Grace, M.D., and Jesse, D.R. (2010). Advances in sediment transport modelling. In:
Journal of Hydraulic Research Vol. 48, No. 6 (2010), pp. 754-763.
Kartezhnikova, M. and Ravens, T. (2013). Hydraulic Impacts of hydrokinetic devices. In: Renewable
Energy Vol. 66 (June, 2014), pp. 425-432.
Kartezhnikova, M. (2013). Hydraulic Impacts of hydrokinetic energy extraction in rivers (thesis, University
of Alaska Anchorage).
TerraSond. (2011). ORPC Hydrokinetic Power Production Project, Physical Characterization Survey:
Tanana River at Nenana, Alaska. Version 1.2, Prepared for Ocean Renewable Power Company. Ref
Type: Report
Toniolo, H. (2013). Bed forms and sediment characteristics along the thalweg on the Tanana River near
Nenana, Alaska, USA. Natural Resources 04, 20-30.
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Appendix: Open-water season discharge data analysis
Ten years period (2003-2014) of open-water season (May- October) flow records were obtained from
USGS River Gage Station 15515500. During this ten years period, the lowest recorded flow value is 198.2
m3/s (May 1, 2013) and the highest flow is 3284.8 m3/s (August 2, 2008). Disregarding the broad range
of recorded discharges, ten years open-season flow data are normally distributed with mean flow of
1312.2 m3/s and median flow of 1325.2 m3/s. Based on this data, discharge records were grouped into
four general categories based on their respective values and frequency of occurrence of each category
was estimated (Figure 15).
Figure 15: Frequency of Tanana river discharge occurrence during the open-water season (May-October)
based on ten years records (2003-2014) on Tanana River, near Nenana, Alaska.
The most common flow rate during the open season on Tanana river is between 1000-1500 m3/s and it
rarely exceeds 2000 m3/s. Table 2 show statistical analyses for each flow group category. Again, mean
and mode values are quite close in each category, excluding the last one (flows higher than 2000 m3/s)
due to the few (five) high flow records around 3000 m3/s.
26%
38%
32%
4%
0%10%20%30%40%
<1000
1000-1500
1500-2000
>2000
Frequancy Q (m3/s) Occurrence (%) of discharge (m3/s) based on open-water season (May-
October) from 2004-2014 on Tanana River, near Nenana, Alaska
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Table 2: Statistical analysis of flow categories of the open-water season (May-October) based on ten
years records (2003-2014) on Tanana River, near Nenana, Alaska.
Category statistic units
Flow groups (m3/s)
<1000 1000-1500 1500-2000 >2000
Mean discharge m3/s 732.15 1253.53 1723.87 2232.82
Median discharge m3/s 731.99 1254.44 1727.34 2132.27
Minimum discharge m3/s 198.22 1005.25 1500.80 2004.84
Maximum discharge m3/s 999.59 1497.97 1999.18 3284.77
Number of records - 394 581 488 67
Frequency % 26 38 32 4
Based on this data it was decided to create sediment transport models for Tanana site at flow rates of
750, 1250, 1750, and 2250 m3/s to investigate and evaluate potential impacts of HK device on Tanana
site during open-water season.