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Assessing GHG exchange at landscape
scale
Bart Kruijt, Ronald Hutjes, Cor Jacobs, Merit van den Berg,
Christain Fritz, Torsten Sachs, Andrei Serafimovich, Stefan
Weideveld, Wilma Jans
Wageningen University&Research; Radboud University
Nijmegen; GeoForschungs Centrum Potsdam
FACCE ERA-GAS
2
ERA-GAS projects
3
Can we optimise the GHG budget of
landscapes?
4
Measuring at landscape scale
 Effects of management
 GHG exchange of the landscape mosaic
Today:
- Peatland emission measures and monitoring
- Simpler flux measurement on small fields
- Integral landscape and fluxes an inventories: aircraft
fluxes
5
Drained peatlands
 Emission Netherlands: 4.2
million ton CO2
 Submerged drains (SMD) a
solution?
Peat
CO2
Peat
Degraded peat
CO2
-60 cm
Ditch
-60 cm
Ditch
Submerged drains
6 m
Winter (wet) Summer (dry)
Business as usual
Effect of submerged drains on water
table and Reco
Translucent soil chamber measurements:
Take light response curves to derive
dark flux
PhD research work, Stefan Weideveld
Pair of eddy covariance sets on peat
meadows with and without submerged drains
8
Routine eddy covariance over multiple
fields...?
9
Simplifying flux measurement:
reviving old ideas.
 Eddy covariance: 𝐹𝑙𝑢𝑥 = 𝑤′ 𝑐′
 Variance methods: 𝐹𝑙𝑢𝑥 = 𝑐𝑜𝑛𝑠𝑡 × 𝜎 𝑐
 Budget methods: 𝐹𝑙𝑢𝑥 =
𝜕𝑐
𝜕𝑡
𝑑𝑡 × 𝑣𝑜𝑙/𝑎𝑟𝑒𝑎
 Surface renewal methods, similar to budget but shorter
time scale:
10
McElrone et al, 2013
Lots of data around to test
 CO2 in-canopy gradients at Loobos pine forest, August
2018 switchover from drought to rains
11
Wall-to-wall landscape fluxes:
Aircraft inventories ...... PH-WUR
12
turbulence probe
Novatel GPS antenna
laser altimeter
infra-red thermometer
net radiation
PAR sensors
LICOR 7500
thermocouple
operator
display
C-Migits
IGPS
antenna
turbulence probe
Novatel GPS antenna
laser altimeter
infra-red thermometer
net radiation
PAR sensors
LICOR 7500
thermocouple
operator
display
C-Migits
IGPS
antenna
And Polar 5 at GFZ Potsdam..
13
Polar 5 in NE Germany
14
Andrej Serafimovich preliminary results
2008 data PH-WUR
Flight Strategy
• Full seasonal cycle, mar08-feb09, weekly flights
• Three routes, representative landscapes
Unique data set
• ~215 flight hours, 40 days, nobs=6102 (after QA)
Stratification
• Temporal m, bm, s
• Soil regions: 5
• 13 LUC types
turbulence probe
Novatel GPS antenna
laser altimeter
infra-red thermometer
net radiation
PAR sensors
LICOR 7500
thermocouple
operator
display
C-Migits
IGPS
antenna
turbulence probe
Novatel GPS antenna
laser altimeter
infra-red thermometer
net radiation
PAR sensors
LICOR 7500
thermocouple
operator
display
C-Migits
IGPS
antenna
Footprint of airborne measurements
Ede
 is footprint model (Kljun, 2004 BLM)
Method Dis-aggregation (DFMR)
 footprint analysis: fractional areas cover class in footprint
of airborne flux observation (right)
 find cover class-specific fluxes FK by multiple regression or
other (constrained) linear solvers (left)
p x 1 vector of airborne
flux observations
p x n matrix of coverclass
fractional areas,
footprint weighted
n x 1 vector of errors
n x 1 vector of coverclass-
specific fluxes
Extrapolate and map fluxes
17
𝑭𝒄 𝒍𝒐𝒄𝒂𝒍
𝑷𝑨𝑹 𝒍𝒐𝒄𝒂𝒍
× PAR 𝒂𝒓𝒆𝒂 = 𝑵𝑬𝑬 𝒂𝒓𝒆𝒂, (DAY!)
(Hutjes & Kruijt in prep)
Airborne NEE and tower validation
18
Hutjes, Vellinga, Elbers
So far: daytime only. How get 24-hour NEE?
 Aircraft can only fly in DAYTIME
 What is lacking is nighttime/ Ecosystem respiration
● Get it from zero-intercept of NEE light response?
● Need to fit non-linear light response on
sparse data – difficult!
● Response is linear on LONGER time scales
● But is that useful?
19
Is night-time NEE predictable from day-
time NEE?
Daytime or GPP fluxes are ‘easy’:
- good turbulence for EC
- Aircraft can fly
- Remote sensing works
- Photosynthesis well understood
 Is NEEnight / NEEday
predictable?
20
A ‘quick look’ at
(NEEnight / NEEday)/night hr
 Analysed a few EC tower data data sets
21
A ‘quick look’ at
abs [(NEEnight / NEEday)/night hr]
 Analysed a few EC tower data data sets
22
(low values)
Vegetated,
MINERAL soil gives
reasonably
consistent ratio.
Peat soil and bare
soil give higher
values
Still some work
to do!
- Comparative flux
measurements at small
fields
- Develop satisfactory
routine measurement
methods
- Extend aircraft flux
inventories to include
nighttime/dark flux
23
24
Annual light response curves...
25
Fit:
𝑁𝐸𝐸 = 𝑅𝑒 0 × 𝑒 𝑐𝑇 + 𝑎 × 𝑃𝐴𝑅

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Assessing GHG exchange at landscape scale

  • 1. Assessing GHG exchange at landscape scale Bart Kruijt, Ronald Hutjes, Cor Jacobs, Merit van den Berg, Christain Fritz, Torsten Sachs, Andrei Serafimovich, Stefan Weideveld, Wilma Jans Wageningen University&Research; Radboud University Nijmegen; GeoForschungs Centrum Potsdam
  • 4. Can we optimise the GHG budget of landscapes? 4
  • 5. Measuring at landscape scale  Effects of management  GHG exchange of the landscape mosaic Today: - Peatland emission measures and monitoring - Simpler flux measurement on small fields - Integral landscape and fluxes an inventories: aircraft fluxes 5
  • 6. Drained peatlands  Emission Netherlands: 4.2 million ton CO2  Submerged drains (SMD) a solution? Peat CO2 Peat Degraded peat CO2 -60 cm Ditch -60 cm Ditch Submerged drains 6 m Winter (wet) Summer (dry) Business as usual
  • 7. Effect of submerged drains on water table and Reco Translucent soil chamber measurements: Take light response curves to derive dark flux PhD research work, Stefan Weideveld
  • 8. Pair of eddy covariance sets on peat meadows with and without submerged drains 8
  • 9. Routine eddy covariance over multiple fields...? 9
  • 10. Simplifying flux measurement: reviving old ideas.  Eddy covariance: 𝐹𝑙𝑢𝑥 = 𝑤′ 𝑐′  Variance methods: 𝐹𝑙𝑢𝑥 = 𝑐𝑜𝑛𝑠𝑡 × 𝜎 𝑐  Budget methods: 𝐹𝑙𝑢𝑥 = 𝜕𝑐 𝜕𝑡 𝑑𝑡 × 𝑣𝑜𝑙/𝑎𝑟𝑒𝑎  Surface renewal methods, similar to budget but shorter time scale: 10 McElrone et al, 2013
  • 11. Lots of data around to test  CO2 in-canopy gradients at Loobos pine forest, August 2018 switchover from drought to rains 11
  • 12. Wall-to-wall landscape fluxes: Aircraft inventories ...... PH-WUR 12 turbulence probe Novatel GPS antenna laser altimeter infra-red thermometer net radiation PAR sensors LICOR 7500 thermocouple operator display C-Migits IGPS antenna turbulence probe Novatel GPS antenna laser altimeter infra-red thermometer net radiation PAR sensors LICOR 7500 thermocouple operator display C-Migits IGPS antenna
  • 13. And Polar 5 at GFZ Potsdam.. 13
  • 14. Polar 5 in NE Germany 14 Andrej Serafimovich preliminary results
  • 15. 2008 data PH-WUR Flight Strategy • Full seasonal cycle, mar08-feb09, weekly flights • Three routes, representative landscapes Unique data set • ~215 flight hours, 40 days, nobs=6102 (after QA) Stratification • Temporal m, bm, s • Soil regions: 5 • 13 LUC types turbulence probe Novatel GPS antenna laser altimeter infra-red thermometer net radiation PAR sensors LICOR 7500 thermocouple operator display C-Migits IGPS antenna turbulence probe Novatel GPS antenna laser altimeter infra-red thermometer net radiation PAR sensors LICOR 7500 thermocouple operator display C-Migits IGPS antenna
  • 16. Footprint of airborne measurements Ede  is footprint model (Kljun, 2004 BLM) Method Dis-aggregation (DFMR)  footprint analysis: fractional areas cover class in footprint of airborne flux observation (right)  find cover class-specific fluxes FK by multiple regression or other (constrained) linear solvers (left) p x 1 vector of airborne flux observations p x n matrix of coverclass fractional areas, footprint weighted n x 1 vector of errors n x 1 vector of coverclass- specific fluxes
  • 17. Extrapolate and map fluxes 17 𝑭𝒄 𝒍𝒐𝒄𝒂𝒍 𝑷𝑨𝑹 𝒍𝒐𝒄𝒂𝒍 × PAR 𝒂𝒓𝒆𝒂 = 𝑵𝑬𝑬 𝒂𝒓𝒆𝒂, (DAY!) (Hutjes & Kruijt in prep)
  • 18. Airborne NEE and tower validation 18 Hutjes, Vellinga, Elbers
  • 19. So far: daytime only. How get 24-hour NEE?  Aircraft can only fly in DAYTIME  What is lacking is nighttime/ Ecosystem respiration ● Get it from zero-intercept of NEE light response? ● Need to fit non-linear light response on sparse data – difficult! ● Response is linear on LONGER time scales ● But is that useful? 19
  • 20. Is night-time NEE predictable from day- time NEE? Daytime or GPP fluxes are ‘easy’: - good turbulence for EC - Aircraft can fly - Remote sensing works - Photosynthesis well understood  Is NEEnight / NEEday predictable? 20
  • 21. A ‘quick look’ at (NEEnight / NEEday)/night hr  Analysed a few EC tower data data sets 21
  • 22. A ‘quick look’ at abs [(NEEnight / NEEday)/night hr]  Analysed a few EC tower data data sets 22 (low values) Vegetated, MINERAL soil gives reasonably consistent ratio. Peat soil and bare soil give higher values
  • 23. Still some work to do! - Comparative flux measurements at small fields - Develop satisfactory routine measurement methods - Extend aircraft flux inventories to include nighttime/dark flux 23
  • 24. 24
  • 25. Annual light response curves... 25 Fit: 𝑁𝐸𝐸 = 𝑅𝑒 0 × 𝑒 𝑐𝑇 + 𝑎 × 𝑃𝐴𝑅