Modeling the export of DOC from large watersheds and its influence on the optical
properties of coastal waters
C.W. Hunt1, W.M. Wollheim2,3, J.S. Salisbury1, R.J. Stewart3, K.W. Hanley4 and G.R. Aiken4
ASLO Session SS54, New Orleans LAFebruary 19, 2013
Study Motivations
River transport of DOC is a major component of global C cycle
River-borne DOC also influences the reactivity and optical properties of inland and coastal ocean aquatic systems
Recent studies* indicate that wetland abundance within small and large catchments is correlated with DOC quantity and quality at the catchment mouth
*Hanley et al. 2013 in review, Buffam et al. 2007
DOC Quality- SUVA254
Little light passes through
sample
Aromatic DOC absorbs strongly
UV light at 254 nm
Image by K.W. Hanley
Study Approach Couple a dynamic hydrological model (FrAMES, 6min) to a
process-based DOC quantity/quality model using parameters found in literature.
Simulate DOC loading as a function of land cover and runoff conditions. Partition DOC quality into Hydrophobic Organic Acids (HPOA, aromatic) and non-HPOA stocks. The %HPOA can be used to derive SUVA254.
Test model in 17 USA watersheds with processing (Respiration and photo-oxidation) turned on and off
Butman et al. 2012
Chapter 1: Large Rivers
OrganicLayer
Mineral Layer
ForestWetlands
Weakly UV-absorbing,DOC-depleted
Strongly UV-absorbing,DOC-enriched
How do wetlands affect DOC quantity and quality?
0 10 20 30 40 50 60 70 800
2
4
6
8
10
12
14
16
18
20
Effect of Runoff on DOC
0mm Runoff4mm Runoff8mm Runoff
Wetland %
DOC
(mg/
l)
TransportLimited Source Limited
HPOA Non-HPOA
River DOC
PhotoRespiration
GPP*
HPOA
Non-HPOA
Local Input
HPOA Non-HPOA
Downstream exports
HPOA Non-HPOA
Upstream inputs
1000 10000 100000 1000000 100000001000
10000
100000
1000000
10000000
f(x) = 0.743263268263621 x + 55788.3457527497R² = 0.961381000365854
Observed Mean DOC flux (kg d-1)
Mod
el M
ean
DOC
flux
(kg
d-1)
Peno
bsco
t Riv
erKe
nneb
ec R
iver
Andr
osco
ggin
Riv
erSu
sque
hann
a Ri
ver
Poto
mac
Riv
erEd
isto
Rive
rAl
tam
aha
Rive
rSt
. Mar
y's
Sant
a Fe
Riv
erM
obile
Riv
erM
ississ
ippi
Riv
erRi
o Gr
ande
Colo
rado
Riv
erSa
n Jo
aqui
n Ri
ver
Sacr
amen
to R
iver
Colu
mbi
a Ri
ver
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
DOC IoASUVA IoA
Inde
x of
Agr
eem
ent
0 5 10 15 20 25 30 35 400
10
20
30
40 DOC Concentration
ModelExponential (Model)ObservedExponential (Observed)
Wetland %
DOC
(mg/
l)
St Mary's River
0 2 4 6 8 10 12 14 16 18 200
10
20 DOC Concentration
ObservedLinear (Observed)ModelLinear (Model)
Wetland %
DOC
(mg/
l)
0 5 10 15 20 25 30 35 400
5
10
15
20
25
30
35
40
f(x) = 0.679893936449303 x + 1.66231722458914R² = 0.951393659317006
DOC Concentration
Observed DOC (mg/l)
Mod
eled
DO
C (m
g/l)
0 2 4 6 8 10 120
2
4
6
8
10
12
f(x) = 0.396646130953876 x + 3.11022498029868R² = 0.575714584837442
DOC Concentration
Without Process-ingLinear (With-out Process-ing)1:1
Observed DOC (mg/l)
Mod
el D
OC
(mg/
l)
0 2 4 6 8 10 120
2
4
6
8
10
12
f(x) = 0.300959202639456 x + 1.36661260020991R² = 0.574656895655416
DOC Concentration
Without Process-ingWith Process-ingLinear (With Process-ing)1:1
Observed DOC (mg/l)
Mod
el D
OC
(mg/
l)
0 1 2 3 4 5 6 7 80
1
2
3
4
5
6
7
8
f(x) = 0.521045105959255 x + 1.14955901270565R² = 0.812369639182967f(x) = 0.478368498350835 x + 1.10253900955503R² = 0.766650536893421
With ProcessingLinear (With Processing)Without ProcessingLinear (Without Processing)1:1
Observed HPOA (mg l-1)
Mod
el H
POA
(mg
l-1)
0 3 250
0
2
10 SUVA254
ObservedPower (Observed)ModelPower (Model)
Wetland% - log scale
SUVA
254
(L*m
gC-1
m-1
) - lo
g sc
ale
Colorado River
St Lawrence River
Conclusions and Future Work
The model shows promise for predicting bulk DOC loading and export at the catchment mouth
Adding two compartments (HPOA and nHPOA) is helpful, but…
There is information we are not capturing in DOC quality (SUVA)
Amazon River Study
From Salisbury et al. 2011
From Salisbury et al. 2011
Model Parameter Values- after Monte Carlo
Parameter Original Monte Carlo test
DOC vs. Wetland% Intercept at low runoff (mg/l) 2.36 2.36
DOC vs. Wetland% Slope at low runoff 0.374 0.55
DOC vs. Runoff asymptote at high flow (mg/l) 6.7 13.5
HPOA% vs. Wetland% .0084*%wet + 0.390 .0084*%wet + 0.390
Photo degredation constant (m-1) 0.001 0.0034
Resp degredation constant (at Tref=30, m/d) 1.47 1.31
Resp degredation constant Q10 2.0 2.0
Monte Carlo Results
0 2 4 6 8 10 120
2
4
6
8
10
12
f(x) = 0.435620690687397 x + 1.83354725243794R² = 0.432048895717466
f(x) = 0.484626433273438 x + 4.94643337362162R² = 0.532170639851622
DOC Concentration- Monte Carlo Params
Without Processing
Linear (Without Process-ing)
With Process-ing
Observed DOC (mg/l)
Mod
el D
OC
(mg/
l)
Monte Carlo Results
1 2 3 4 52
3
4
5
6
7
8
f(x) = − 0.0616244411795221 x + 5.52961375451189R² = 0.00479866938491946
f(x) = 0.538341295194449 x + 3.78355831281822R² = 0.205120734254932
SUVA - Monte Carlo Params
Monte Carlo ParamsLinear (Monte Carlo Params)Lit ParamsLinear (Lit Params)1:1
Observed SUVA
Mod
el S
UVA
ReferencesButman, D., Raymond, P.A., Butler, K. and G. Aiken. 2012. Relationships between Δ14C and the molecular quality of dissolved organic carbon in rivers draining to the coast from the conterminous United States. Global Biogeochemical Cycles, 26: GB4014.
Hanley, K.W., Wolheim, W.M., Salisbury, J., Huntington, T., and G. Aiken. 2013. Controls on dissolved organic carbon quantity and quality in large North American rivers. Global Biogeochemical Cycles, in review.
Raymond, P.A. and J.E. Saiers. 2010. Event controlled DOC export from forested watersheds. Biogeochemistry dio 10.1007/s10533-010-9416-7.
Salisbury, J., Vandemark, D., Campbell, J., Hunt, C.W., Wisser, D., Reul, N., and B. Chapron. 2011. Spatial and temporal coherence between Amazon River discharge, salinity, and light absorption by colored organic carbon in western tropical Atlantic surface waters. J. Geophys. Res. 116: COOHO2.
Methods
• The fraction of DOC as hydrophobic organic acids (HPOA%) was determined according to Hanley et a. 2012:
• HPOA% = ((1.19 * log10(wetlands%)) + 3.762) / 8.792
• Finally, the specific ultraviolet absorbance of DOC at 254 nm, an indicator of DOC aromaticity, was estimated:
• SUVA-254=(HPOA% * 8.792) - 1.126
*from Hanley et al. 2013 in press
Processing and DOC Quality
DOC (HPOA) DOC (non-HPOA)
Upstream DOC
(HPOA)
Upstream DOC (non-
HPOA)
Photodegradation
GPP* Resp
Water Balance Model (WBM)
Vorosmarty et al. 1998 (Appendix B)
FrAMES
Water Transport Model (WTM, STN)
Vorosmarty et al. 2000
Other functions*
“Vertical” movement of water (precip, ET, etc.)
Wollheim et al. 2008Wisser et al. 2009Stewart et al. 2011
“Horizontal” movement of water (river network routing
using STN or Simulated Topological Network)
Nitrogen, Reservoirs, Transient Storage
* These are often embedded within WBM, WTM
1. 2.
1.
2.
Grid Cell
SnowmeltET
Rooting Zone
Shallow Groundwater Detention Pool
Snowpack
Recharge
Precipitation
WBM Grid Cell
Parameter Value or formula Source
DOC vs. Wetland% Intercept at low runoff (mg/l) 2.36 Raymond and Saiers 2010
DOC vs. Wetland% Slope at low runoff 0.374
Composite of Eckhardt and Moore 1990, Buffam et al 2007, and Raymond and Hopkinson 2003
DOC vs. Runoff asymptote at high flow (mg/l) 6.7 Raymond and Saiers 2010, at peak flow of 8 mm/d
HPOA% vs. Wetland% .0084*%wet + 0.390 Wollheim (Ipswich-Parker river data)
Photo degredation constant (m-1) 0.001 Literature composite
Resp degredation constant (at Tref=30, m/d) 1.47 Literature composite
Resp degredation constant Q10 2.0 Literature composite
Model Parameter Values
Soil Organic Matter
Riverine DOC
Sources of DOC in Rivers
Image by K.W. Hanley
Without wetlands, DOC removal and fractionation can occur in the subsurface…
Organic HorizonMineral Horizon
DOC added to new groundwater
1.
DOC transported out of organic horizon
2.
Preferential sorption of humic and fulvic acids to mineral soils
and extensive microbial processing
3.
Weakly UV-absorbing, DOC-depleted
groundwater enters stream
4.
With wetlands, DOC depletion and fractionation are less likely…
Organic Horizon
Mineral Horizon
DOC added to new groundwater
1.
Subsurface flow through deep and often anaerobic organic horizon -
little sorption or microbial processing
2.
Strongly UV-absorbing, DOC-rich groundwater
enters stream
3.
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