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Tidal Wetland Biogeochemistry in High Definition: Using High-Frequency Measurements to Estimate Biogeochemical Rates
Brian Bergamaschi, Bryan Downing, Tamara Krausand many, many, many others; several in the room
A special thanks to and remembrance of George Aiken, without whom my career would have taken a very different and less salubrious path
New and Emerging Tools and Techniques for the Study of Biogeochemistry in Wetlands
OutlineIntroduction
Rate determination using continuous in situ measurements and proxies
Rate determination using mapping together with residence time techniques
Rate determination using multiple continuous sensor deployments and hydrodynamic models
New and revisited efforts
Final thoughts
Biogeochemical Rates
• Emergent marsh• Marsh plain• Submerged aquatic
vegetation• Small dendritic sub channels• Inter-tidal mudflats
South Bay
NO3 (mg-N/L)
Assess how marsh interactions affect aquatic ecosystems as related to landscape elements, hydrodynamics and geomorphology
• Export production• Nutrient cycling• Sediment trapping• Contaminant yield
• Mercury• Carbon and GHG balance
LandscapeRate
In situ measurements
Commercially-available submersible instruments:• Fluorometers – single and multiple wavelength; custom• Spectrophotometers – UV and UV-vis• Wet chemistry• Optodes
Wavelength (nm)
0.0
0.2
0.4
0.6
0.8
1.0
200
250
300
350
400
450
500
550
600
650
700
UVA254
Spectral Slope
Inte
nsity
Fluorescence
-2
-1
0
1
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3
0
5
10
15
20
25
9/30/2014 10/2/2014 10/4/2014 10/6/2014 10/8/2014 10/10/2014 10/12/2014
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-1
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9/30/2014 10/2/2014 10/4/2014 10/6/2014 10/8/2014 10/10/2014 10/12/2014
-2
-1
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1
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9/30/2014 10/2/2014 10/4/2014 10/6/2014 10/8/2014 10/10/2014 10/12/2014
-2
-1
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9/30/2014 10/2/2014 10/4/2014 10/6/2014 10/8/2014 10/10/2014 10/12/2014
-2
-1
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250
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350
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9/30/2014 10/2/2014 10/4/2014 10/6/2014 10/8/2014 10/10/2014 10/12/2014
-2
-1
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500
9/30/2014 10/2/2014 10/4/2014 10/6/2014 10/8/2014 10/10/2014 10/12/2014
NITRATE
CHLORO-PHYLL
OXYGEN
CO2
DISSOLVEDORGANIC CARBON
PARTICLESIZE
LITTLE HOLLAND TRACT
Nitrate uptake on LHT
Chlorophyll productionon LHT and export
Net production on LHTVariable over time
DIC drawdown on LHTAquatic production
DOC production on LHTExport of DOC
Larger particles coming onto LHT; export of smaller particles
TIDAL FLUX
Rate determination using continuous in situ measurements and proxies
PROXY MEASUREMENT: Methylmercury export
Bergamaschi et al., 2011,
Proxy measurements for high resolved MeHg flux from a tidal wetland, Browns Island, CA
PROXY MEASUREMENT:All mercury species and phases
DISSOLVED UNFILTERED PARTICULATE
Bergamaschi et al., 2011,
Concentration
X
Discharge
Flux
(Downing et al., 2009)
Methylmercury fluxes and yieldsYIELDS:
2.5 μg m-2 yr-1
4-40 times previously published yields
Bergamaschi et al., 2011Bergamaschi et al., 2012
Variation related to:TidesRiver flowStormsWind directionBarometric pressure
Rate determination using mapping together with residence time techniques
Water Quality in the Study Area
0.30 0.70
Nitrate (mg/L)
1.80 9.00
FCHLA (ug/L) d at tude Co o s o s deta
70.00 102.00
EXO DO % a d at tude Co o s o s de
170.0 400.0
Sp Conductivi..
5.00 40.00
FDOM (QSU)
Mapping of water isotopes δ18O and δ2H
-79.47 -60.43
δ2H
-10.742 -7.116
δ18O
From water isotope ratios to residence time
δ2𝐻𝐻 𝑜𝑜𝑜𝑜 δ18𝑂𝑂 =𝑅𝑅𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑅𝑅𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑜𝑜𝑠𝑠
− 1
Evaporation:Inflow (E:I) ratio Steady-State.(e.g. Brooks et al, 2014)
𝐸𝐸𝐼𝐼
=δ𝐼𝐼 − δ𝐿𝐿
𝑠𝑠(δ ∗ −δ𝐿𝐿)
τ = %𝐸𝐸×𝐷𝐷𝐸𝐸𝐸𝐸𝐸𝐸×1.1 CIMIS ETo DataDowning et al. ES&T (2016)
Nitrate uptake rates
Net Ecosystem Nitrate Uptake
0.5
0.6
0.7
0.8
0.9
1
1.1
0 10 20 30 40
Frac
tion
Nitr
ate
Rem
aini
ng
Water Residence Time (d)
Prospect Slough
Shag Slough
Deep Water Ship Channel
Why are rates different?
tidal wetlandsaquatic vegetation
Where rate (k): 𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅
= 𝒌𝒌𝒅𝒅 and 𝒅𝒅𝒅𝒅 = 𝒅𝒅𝟎𝟎𝒆𝒆−𝒌𝒌𝒅𝒅 :
Whole-ecosystem uptake rates (k) ranged from 0.006 to 0.039 d−1.
Downing et al. ES&T (2016)
Rate determination using multiple continuous sensor deployments and hydrodynamic models
Estimating nitrification rates from nitrate changes down river
WGAFPTFlow
(Kraus et al., 2017)
Change in nitrate
∆𝑁𝑁𝑁𝑁3
∆𝑁𝑁𝑁𝑁3 𝑠𝑠
(Kraus et al., 2017)
Travel time model for tidal system
𝑠𝑠𝑡𝑡 = 𝑠𝑠 ∗ �𝑘𝑘𝑚𝑚=0
29
𝑣𝑣𝑓𝑓𝑓𝑓𝑡𝑡 ∗ 𝑠𝑠𝑠𝑠𝑓𝑓𝑓𝑓𝑡𝑡29
+ 𝑣𝑣𝑤𝑤𝑤𝑤𝑤𝑤 ∗ 𝑠𝑠𝑠𝑠𝑤𝑤𝑤𝑤𝑤𝑤
29
Nitrification ∆𝑁𝑁𝑁𝑁3 = 𝑘𝑘𝑁𝑁𝑁𝑁𝐸𝐸
𝑁𝑁𝐻𝐻4+𝑠𝑠𝑉𝑉𝑡𝑡
+
𝑘𝑘𝑁𝑁𝑁𝑁 𝑂𝑂𝑁𝑁 𝑠𝑠 − 𝑘𝑘𝑈𝑈,𝑁𝑁𝑁𝑁3−2 𝑁𝑁𝑂𝑂3−2 𝑠𝑠 −
𝑘𝑘𝐷𝐷𝑁𝑁,𝑁𝑁𝑁𝑁3−2 𝑁𝑁𝑂𝑂3−2 𝑠𝑠
Region Method Nitrification Rate (mg-N/L-d) Season Reference
Sacramento River, CaliforniaNet Transformation 0.026 ± 0.011-0.045 ± 0.012
September 2013 - September 2014 This study 2015
Puget Sound, Washington 15-N 0.000112-0.00581May, August, October, December Urakawa et al. 2014
Chang Jiang River, China 15-N up to 0.064 August, after typhoon Hsiao et al. 2014
San Francisco Bay Delta, California
Net Transformation
0.056 (net transformation) 0.090 (nitrification factor) March-April 2009 Parker et al. 2012
Scheldt Estuary, France 15-N 0.032-0.236January, April, July, October 2003 Andersson et al. 2006
Rhone River, Northwest Mediterranean Sea 14-C up to 0.058
November 1991-October 1992 Bianchi et al. 1999
Urdaibai Estuary, Spain 14-C 0.00028-0.065 August 1994 Iriarte et al. 1996
Rhone River, Northwest Mediterranean Sea 14-C 0.014-0.028 May 1992
Fliatra and Bianchi 1993
Tamar Estuary, England, UK 14-C up to 0.042 May-August 1982 Owens 1986
Delaware River, New Jersey 15-N 0.0154-0.0266 July and September 1983 Lipschultz et al. 1986
Table 6. Nitrification rates reported in the literature.0
0.1
0.2
0.3m
g-N
L-1
d-1
Nitrification rates from the literature
Nitrification rate and Temperature
5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
0.0000
0.0005
0.0010
0.0015
0.0020
0.0025
0.0030
0.0035
0.0040
0.0045
0.0050
0.0055
N
Temperature
Nitr
ifica
tion
rate
Connecting to Remote Sensing
Fichot, C. G., B. D. Downing, B. A. Bergamaschi, L. Windham-Myers, M. Marvin-DiPasquale, D. R. Thompson, and M. M. Gierach (2015), High-Resolution Remote Sensing of Water Quality in the San Francisco Bay–Delta Estuary, Environmental Science & Technology, doi:10.1021/acs.est.5b03518.
Benthic chamber – real time flux measurementsBenthic fluxes
y = 147.44x R² = 0.96
33
34
35
36
37
38
39
14:24 14:38 14:52 15:07 15:21
Nitr
ate
(uM
)
Time
Figure 3. Graph showing change in nitrate concentration over time.
Final Thoughts• New innovative methods are needed to understand the coupling of
wetlands with pelagic aquatic systems• Many improvements are needed in current methods• Especially to improve scalability and transferability
• New instrumentation provides new opportunities• We need to be creative in their use
• High resolution data is needed to bound variability• Continuous measurements are necessary• tidal systems are dynamic – cannot extrapolate from one or a few tides
and get the right answer • Water age/residence time is an important driver of biogeochemical
processes in wetlands• Should include in our studies
• Systematic methods are needed for scaling from plot-based to landscape-scale assessments
• Typological models of wetland geomorphology and hydrodynamics• Need many additional studies using common techniques
papers available at: http://profile.usgs.gov/bbergama/
mailto:[email protected]
Residence time (τ)
North Bay
South Bay
Delta
τ (days)
Ed Gross, 2018. RMADowning et al., 2016
Gross et al., 2018 (in prep)
Isotope Model
Presence and Absence of Wastewater
• Multiple WW holds during study period
• ~30 holds• >7 hours• ~ 5 km parcel
of wastewater free water
FDOM
Areas needing improvement
o Better constraints on yield areao Soil drainage rateso Improved calculationso Model integration
o Longer records from different systems o Magnitude of variabilityo Modes and drivers of variation
o Models o Wetland typologyo Critical characteristics
• Because you need to• even for loads……C:Q often doesn’t work.• In tidal systems……….fuhgetaboutit
• Separate among multiple modes of variability in ecological drivers
• Understand and quantify fluxes and process rates• Identify long term trends• IMPROVE DISCRETE SAMPLING
• Identify appropriate sampling timing and frequency• Establish linkages between discrete samples• Place discrete sampling to environmental and hydrologic context
and relate to antecedent conditions
Why measure in?
Nitr
ate
(µM
)
-10
-5
0
5
10
15
20
25
Wat
er d
epth
(m
)
0.0
0.5
1.0
1.5
2.0
2.5
Tidal Wetland Biogeochemistry in High Definition: Using High-Frequency Measurements to Estimate Biogeochemical Rates OutlineBiogeochemical RatesSlide Number 4In situ measurementsSlide Number 6Slide Number 7Slide Number 8Slide Number 9Slide Number 10Slide Number 11Slide Number 12Water Quality in the Study AreaSlide Number 14Slide Number 15Slide Number 16Slide Number 17Estimating nitrification rates from nitrate changes down riverChange in nitrate Travel time model for tidal systemSlide Number 21Nitrification rate and TemperatureSlide Number 23Slide Number 24Final ThoughtsTHANKS!Residence time (τ)Presence and Absence of WastewaterSlide Number 29Slide Number 30