Coupling Suspended Sediment Dynamics and Light Penetration in the Upper
Chesapeake Bay
Charles L. Gallegos
Smithsonian Environmental Research Center
Photos by Grace Cartwright
Outline• Review
• Model Refinement
• Field Work–Potomac findings
–Baywide extension
• Summary
Elements of Radiative Transfer Modeling in Natural Waters
• Radiative Transfer Equations perform an energy balance on an infinitesimal solid angle, accounting for gains and losses
• First-order effects are governed by the magnitude of inherent optical properties (IOPs): absorption coefficient, scattering coefficient, and scattering phase function (principally, backscattering:total scattering ratio)
• Primary water quality determinants of the IOPs are colored dissolved organic matter (CDOM), phytoplankton pigments, and other particulates (detritus, suspended minerals).
Inherent Optical Properties
esParticulat algal-NonPhytoCDOMwatertotal aaaaa
Absorption Coefficient
•Water: From published tables (Pope and Fry 1997)
Laboratory
In Situ (total-water)•WETLabs Spectral ac-9
•CDOM: Spectrophotometric with long path cell•Particulate: Filter pad method
Inherent Optical Properties
tp acb Particulate Scattering
Beam Attenuation
Total Absorption
Scattering Coefficient
Also measured using WETLabs ac-9 in situ or in laboratory.
Inherent Optical PropertiesScattering Phase Function, ()/b
• Probability distribution of scattered photons
• Strongly peaked in the forward direction
• Well specified by the ratio of backscattering:total scattering, bb/b
• Measured in situ by HOBILABS Hydroscat-6 or WETLabs ECO-VSF-3
Backscattering,
bb
Forward scattering,
bf
bf
bf
bb
bbb
Kd Relationship Revisited:Parameterize effects of variations in…
• Solar incidence angle, µ0
• Relative proportion of scattering and absorption, principally b:a ratio
• Backscattering ratio, bb:b
• Optical depth, c·z
• Direct and diffuse incident light*--New complexity
New Bio-optical Model is Based On*:
0 b
zd
baK
Depends on: optical depth, backscattering ratio, solar zenith angle, and scattering:absorption ratio.
Ratio backscattering:total scattering
Cosine in-water solar zenith angle
*—Albert, A., and C. D. Mobley. 2003. An analytical model for subsurface irradiance and remote sensing reflectance in deep and shallow case-2 waters. Optics Express 11: 2873-2890.
Implementation
• Algorithm has 33 equations due to multiple dependencies of z on other parameters (i.e. bb/b, b/a, etc.)
• Some of the governing parameters, e.g. backscatter ratio, are poorly represented in data
• Solution at each cell and time step would place excessive drag on complete model
Look-up Table Approach• Used bio-optical model to generate Kd values for
a range of inherent optical properties in nested loops of:– I: Cosine solar angle (8 bins, 0.71-0.91)– J: CDOM (20 bins, 0.1-8 m-1)– K: Chlorophyll absorption (35 bins, 0.02-18.4 m-1)– L: Particulate scattering (35 bins, 0.6-570 m-1)– M: Particulate absorption:scattering ratio (10 bins,
0.06-0.24)
• Resulting array consists of 1,960,000 values of Kd(PAR)
Lookup Table Approach cont’d.
• Initialize:– Read in Kd(PAR) array
– Read in season- and segment-specific inherent optical properties
• From date, segment, and water quality (CDOM, chlorophyll & TSS), search bins to find I, J, K, L, & M
• Look up Kd(PAR) in array
Lookup Table Approach cont’d.Must Determine…
• Absorption by CDOM• Absorption by chlorophyll
– Product of specific-absorption coefficient and chlorophyll concentration
• Scattering by particulates– Product of specific-scattering coefficient and TSS
concentration
• Absorption by non-algal particulates– Product of scattering and absorption:scattering ratio
Need: CDOM absorption, and specific-absorption and –scattering coefficients on segment and season basis
CDOM Concentrations: Potomac
0 20 40 60 80 100 120 1400.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
Distance Below Fall Line (km)
ag(4
40
) (m
-1)
Mar04 Jun04 Aug04 Mar05 Jun05 Sep05
• Seasonal variability>>Spatial
• Current sampling program expected to be adequate characterization
Bay-wide Extension: Sample Coverage
CDOM Absorption: Bay-wide
Chlorophyll-specific Absorption: Potomac
0 2 4 6 8 10 12 14 16 180.0
0.1
0.2
0.3
0.4
0.5
a (6
75)
(m-1
)
Chlorophyll (mg m-3)
March June Aug-Sep
a*(675) = 0.028 m2 mg-1 Mar-Jun
0.018 m2 mg-1 Aug-Sep
0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.0902468
101214161820222426283032
Fre
quen
cya
*(675) m2 (mg Chl)-1
Ensemble mean: 0.030 m2 mg-1
Forced zero-intercept Regressions
*Point-estimate a(675)/[Chla]
*—Necessary when sample size is small
Chlorophyll-specific Absorption: Bay-wide
Particulate Scattering: Potomac
0 50 100 150 200 250
0
20
40
60
80
100
120
bp(5
55)
(m-1)
TSS (g m-3)
Mar JunAug-Sep
20 40 60 80 100 1200.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
b p* (555
) (m
2 g-1)
km Below Fall Line
•Forced zero-intercept: = 0.57 m2 g-1
•Ensemble average of point-estimates = 0.94 m2 g-1
•Varies systematically along river axis
Particulate Scattering: Bay-wide
NAP Absorption:Scattering Ratio: Potomac
0 2 4 6 8 1012141618202224262830323436380.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
a p-(
440)
(m
-1)
bp(555) (m-1)
Mar Jun Aug-Sep
555
440
p
p
b
aPCI Define “Particle Color Index”, PCI,
•From forced zero-intercept regression, PCI=0.088
•Ensemble average, PCI=0.12
•Variability principally temporal
2 3 4 5 6 7 8 9 100.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
PC
I
Month
NAP Absorption:Scattering Ratio: Bay-wide
Light Attenuation Model EvaluationBased on Measured Coefficients—Potomac River
0 1 2 3 4 50
1
2
3
4
5
Sim
ulat
ed K
d(P
AR
) (m
-1)
Measured Kd(PAR) (m-1)
• 2004 data
• Slope (model vs. obs.) = 0.98, r2=0.75
• Used measured, station-averaged coefficients
Light Attenuation ModelBay-wide Extension Based on Look-up Table Approach
1 10
1
10
Model Ref Reps
Mod
eled
Kd(
PA
R)
(m-1)
Measured Kd(PAR) (m-1)Chesapeake Bay Program Data
5,873 Observations
1995-1999
Backscatter Fraction: Potomac
8 8
3 2 22 2
2 35
3 3 3
LE2.
3
LE2.
2
PR
01
PR
02
PR
03
PR
04
PR
05
PR
06
PR
07
PR
08
PR
09
PR
10
PR
11
0.000
0.005
0.010
0.015
0.020
0.025
Bac
ksca
tter
Fra
ctio
n, b
b/b
Station
• Difficult to measure in RET/TF sections of river due to high concentrations of TSS saturating instrument
• Available data indicates systematic longitudinal gradient
• Direct measurements unavailable elsewhere, except CB4MH (average=-.0125)
LE2.
3
LE2.
2
PR
01
PR
02
PR
03
PR
04
PR
05
PR
06
PR
07
PR
08
PR
09
PR
10
PR
11
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
Pre
dic
ted
Kd(P
AR
) (m
-1)
Station
Implications for Prediction of Kd(PAR)
Constant Water Quality Assumed:
CDOM=0.5 m-1; Chla=6 mg m-3; TSS=12.7 g m-3; based on 6/15/05, PR04
• Ca. 30% change in simulated Kd(PAR) due to changes in bb/b alone
• For assumed condition, change crosses SAV Tier II habitat requirement
To Do
• Re-generate Kd for Lookup Table varying backscatter ratio, bb/b
• Modify Lookup Table routine to take advantage of further bb/b data as it becomes available
Symbols for diagrams courtesy of the Integration and Application Network (ian.umces.edu/symbols), University of Maryland Center for Environmental Science.