1 A Turbidity Model A Turbidity Model For Ashokan For Ashokan Reservoir Reservoir Rakesh K. Gelda, Steven W. Effler Rakesh K. Gelda, Steven W. Effler Feng Peng, Emmet M. Owens Feng Peng, Emmet M. Owens Upstate Freshwater Institute, Syracuse, NY Upstate Freshwater Institute, Syracuse, NY Donald C. Pierson Donald C. Pierson New York City Department of Environmental New York City Department of Environmental Protection Protection 2009 Watershed Science & Technical Conference 2009 Watershed Science & Technical Conference September 14 September 14 th th -15 -15 th th , , Thayer Hotel, West Point, New York Thayer Hotel, West Point, New York
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1 A Turbidity Model For Ashokan Reservoir Rakesh K. Gelda, Steven W. Effler Feng Peng, Emmet M. Owens Upstate Freshwater Institute, Syracuse, NY Donald.
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A Turbidity Model For A Turbidity Model For Ashokan ReservoirAshokan Reservoir
Rakesh K. Gelda, Steven W. EfflerRakesh K. Gelda, Steven W. EfflerFeng Peng, Emmet M. OwensFeng Peng, Emmet M. Owens
Upstate Freshwater Institute, Syracuse, NYUpstate Freshwater Institute, Syracuse, NY
Donald C. PiersonDonald C. PiersonNew York City Department of Environmental ProtectionNew York City Department of Environmental Protection
2009 Watershed Science & Technical Conference2009 Watershed Science & Technical ConferenceSeptember 14September 14thth-15-15thth,,Thayer Hotel, West Point, New YorkThayer Hotel, West Point, New York
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• network of 19 reservoirsnetwork of 19 reservoirs• three controlled lakesthree controlled lakes• Croton, Catskill, Delaware Croton, Catskill, Delaware systemssystems• watershed: 1930 miwatershed: 1930 mi22
Turbidity ProblemTurbidity Problem stream channel and banks erosion – glacial and fluvial stream channel and banks erosion – glacial and fluvial
sediment; Esopus Creek 85% of the inflowsediment; Esopus Creek 85% of the inflow turbidity in waters leaving Ashokan Reservoir can be high turbidity in waters leaving Ashokan Reservoir can be high
following major runoff eventsfollowing major runoff events alum treatment before it enters Kensico – Nine alum events, alum treatment before it enters Kensico – Nine alum events,
524 days during 1987-2007524 days during 1987-2007 turbidity model to evaluate management alternativesturbidity model to evaluate management alternatives
1010
Features of Turbidity ModelFeatures of Turbidity Model
Two-dimensional (longitudinal-vertical), laterally Two-dimensional (longitudinal-vertical), laterally averaged transport framework (CE-QUAL-W2)averaged transport framework (CE-QUAL-W2)
State variables: Temperature (T) and turbidity (Tn)State variables: Temperature (T) and turbidity (Tn) Three size classes of TnThree size classes of Tn Source of Tn: external loadingSource of Tn: external loading Sinks: settling, export (via withdrawal, spill, waste Sinks: settling, export (via withdrawal, spill, waste
channel diversion)channel diversion) Two basins simulated separatelyTwo basins simulated separately
1111
Model Grid – West BasinModel Grid – West Basin
2
3
45
6
7
89
1011
1213
1415
1617 18
1920
2122
2324
2526
2728
27 segments (~330 m avg)47 layers (1 m)1 branch
Esopus Creek
dividing weirdividing weir
1212
Model Grid – East BasinModel Grid – East Basin
2 34
56
78
910
1112
1314
1516
1718
1920
2122
2324
2526
2728 29 30 3132 33 34 35 36 37
38
37 segments (~ 300 m avg)26 layers (1 m)1 branch
spill
dividing dividing weirweir
1313
Model Grid – Vertical LayersModel Grid – Vertical LayersDistance from weir (m)
0 2000 4000 6000 8000 10000 12000
Ele
vatio
n (m
)
130
140
150
160
170
180
div
idin
g w
eir
west basin east basin
1414
Turbidity (Tn)Turbidity (Tn) primary metric of quality for water suppliesprimary metric of quality for water supplies measure of light scattering by particles at 90° collection measure of light scattering by particles at 90° collection
angle, units of NTUangle, units of NTU
Tn Tn α α bb;; supported in peer-reviewed literature supported in peer-reviewed literature bb, Tn = , Tn = f f (particle concentration, size distribution, (particle concentration, size distribution,
composition, shape)composition, shape)
0°
90°
incident beam
scattered light
1Tn Tn αα
light scattering coefficient (b, m-1)
1
360
0bb
1515
Scattering (Scattering (bb) and Turbidity (Tn): ) and Turbidity (Tn): Behaves Like Intensive PropertiesBehaves Like Intensive Properties
mass balance calculations can be donemass balance calculations can be done well-established in optical literature (well-established in optical literature (Davies-Colley et al. 1993Davies-Colley et al. 1993))
Q1, b1, Tn1
Q2, b2, Tn2
Q, b, Tn
example
Q
bQbQb 2211
Q
TnQTnQTn 2211
Q = Q1 + Q2
1616
Turbidity: As the Model State VariableTurbidity: As the Model State Variable
Tn is the regulated parameterTn is the regulated parameter
disadvantages of TSS (a gravimetric measurement) as an disadvantages of TSS (a gravimetric measurement) as an alternative (would have to rely on Tn = alternative (would have to rely on Tn = kk · TSS) · TSS)
differences in particle size and composition dependencies of Tn differences in particle size and composition dependencies of Tn and TSSand TSS
Tn, Tn, bb (scattering) and (scattering) and cc (beam attenuation) measurements more (beam attenuation) measurements more preciseprecise
limitations in temporal and spatial resolution; e.g., robotic and limitations in temporal and spatial resolution; e.g., robotic and rapid profiling capabilities for Tn and rapid profiling capabilities for Tn and cc
pore size for TSS measurements too large (1.7 µm)pore size for TSS measurements too large (1.7 µm) variation in relationship between Tn and TSS in time and space variation in relationship between Tn and TSS in time and space
(i.e., (i.e., kk is not really a constant) is not really a constant)
Tn, [and Tn, [and cc] supported in peer-reviewed literature, without ] supported in peer-reviewed literature, without published critical commentspublished critical comments
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Model InputsModel Inputs Model testing period: 2003-2007Model testing period: 2003-2007
supported by UFI’s intensive (Robohut on Esopus Creek, in-supported by UFI’s intensive (Robohut on Esopus Creek, in-reservoir robots) and DEP’s routine monitoring datareservoir robots) and DEP’s routine monitoring data
constrained by the availability of operations dataconstrained by the availability of operations data Additional (secondary) validation period: 1995-2002Additional (secondary) validation period: 1995-2002
Operations data Operations data Hydrologic inputs/outputsHydrologic inputs/outputs Loading of turbidityLoading of turbidity Creek temperature Creek temperature Meteorological dataMeteorological data
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In-Reservoir Robots: Example, 2007In-Reservoir Robots: Example, 2007
site 2
site 1.4
site 3.1
site 4.2
April – November (June in 2007)depth-profiles every 6 hoursdepth interval 1 m
““Turbidity” Size-Classes for ModelTurbidity” Size-Classes for Model
0.1 1 10
0
20
40
60
80
100
Cum
ulat
ive b m
(660
) (%
)
Particle size (m)
ClassClass size size (µm)(µm)
Size Size rangerange
velvel
(m/d)(m/d)
11 11 < 1.75< 1.75 0.0750.075
22 3.143.14 1.75-1.75-5.755.75
0.750.75
33 8.118.11 > 5.75> 5.75 5.05.0
ClassClass Q ≤ 40 Q ≤ 40 mm33/s/s
Q > 40 Q > 40 mm33/s/s
11 10%10% 10%10%
22 65%65% 45%45%
33 25%25% 45%45%
Fractions in Esopus CreekFractions in Esopus CreekStokes Law:
18/)( 2dgSV wp
coefficient specification constrained by coefficient specification constrained by reality of particle characteristics as reality of particle characteristics as obtained from IPAobtained from IPA
Esopus Creek
2323
Hydrothermal Model PerformanceHydrothermal Model Performance
Predicted Tw (°C)
0 5 10 15 20 25
Obs
erve
d T
w (
°C)
0
5
10
15
20
25(b)2003-2007r2 = 0.98RMSE = 1.20 °C
Predicted Tw (°C)
0 5 10 15 20 25
Obs
erve
d T
w (
°C)
0
5
10
15
20
25(c)1995-2002r2 = 0.95RMSE = 1.99 °C
* withdrawal temperature (Tw)* importance of withdrawal depth information
2003-2007 1995-2002
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Turbidity Model PerformanceTurbidity Model Performance* withdrawal turbidity (Tn,w)* importance of detailed monitoring of forcing conditions
2003-2007
Predicted Tn,w (NTU)10 100
Ob
serv
ed T
n,w (
NT
U)
10
100
r2 = 0.81 RMSE = 9.5 NTU
1995-2002
Predicted Tn,w (NTU)10 100
Ob
serv
ed T
n,w (
NT
U)
10
100
r2 = 0.48 RMSE = 13.2 NTU
2525
Turbidity Model PerformanceTurbidity Model Performance
Turbidity Model Turbidity Model PerformancePerformance
10
10
10
10
20
20
20
30
4050
6070
40
50
8090
100
Distance from dividing weir (km)
0 1 2 3 4 5 6 7 8
Ele
vatio
n (m
)
150
165
180
10
10
1020
20
20
10
30
4050
1020
30
60
2010
60
10
20
20
10
70
70
8080
20
80
Distance from dividing weir (km)0 1 2 3 4 5 6 7 8
Ele
vatio
n (m
)
150
165
180
observed Tn on 6/30/06 (east basin)
predicted Tn on 6/30/06 (east basin)
East Basin6/30/2006
2727
Alum treatment events
*
* Normalized RMSE (Gelda and Effler, 2007)
performance for well monitored years consistent with that reported for Schoharie Reservoir (Gelda and Effler, 2007)
Performance SummaryPerformance Summary
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SummarySummary
2-D model CE-QUAL-W2 as transport framework2-D model CE-QUAL-W2 as transport framework Turbidity as a state variableTurbidity as a state variable Characterization of turbidity-causing particlesCharacterization of turbidity-causing particles Three size classesThree size classes Model performed well in simulating in-reservoir and Model performed well in simulating in-reservoir and
withdrawal temperature and turbiditywithdrawal temperature and turbidity Model is suitable for evaluating management alternativesModel is suitable for evaluating management alternatives Future research: resuspension, particle-based modeling Future research: resuspension, particle-based modeling
including aggregationincluding aggregation
Gelda, R. K., S. W. Effler, F. Peng, E. M. Owens and D. C. Pierson, 2009. Turbidity Gelda, R. K., S. W. Effler, F. Peng, E. M. Owens and D. C. Pierson, 2009. Turbidity model for Ashokan Reservoir, New York: Case Study. J. Environ. Eng. model for Ashokan Reservoir, New York: Case Study. J. Environ. Eng. 135:135: 885-895. 885-895.