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Modelling of growing season methane fluxes in a high-Arctic wet tundra ecosystem 1997–2010 using in situ and high-resolution satellite data Cover

Modelling of growing season methane fluxes in a high-Arctic wet tundra ecosystem 1997–2010 using in situ and high-resolution satellite data

Tellus B: Chemical and Physical Meteorology
Volume 65 (2013): Issue 1
By: ,  ,  ,  ,  ,  ,  ,  ,  ,  ,  ,   and    
Open Access
|Jan 2013
Figures & tables

Figures & Tables

Fig. 1

The Zackenberg valley and the investigation area surrounding the research station (ZERO). The field inventory map of the dominant plant communities estimated in the Rylekærene study site is superimposed over the area. The vegetation map is the studied area referred to as Rylekærene throughout the text. The red dot on the Greenland map is the location of Zackenberg. The Footprint areas are the average 80% cumulative flux distances of the two towers.

Fig. 2

Average (±1 SD) normalised NDWI based on MODIS surface reflectance data 2000–2010. Data was averaged for each 8-d period after DOY of snowmelt and it was normalised against the seasonal average NDWI. The dotted lines show the time window used for choosing high-resolution Landsat data day 38–55 after DOY of snowmelt.

Table 1

The different sensors recording the Landsat images that were used in the analysis

Year Satellite sensorDOY of Landsat imageDOY with 10 cm snow depth1997Landsat 5 TM222170a2000Landsat 7 ETM+2041652002Landsat 7 ETM+2141712007Landsat 7 ETM+c2101592008Landsat 7 ETM+c2221752009Landsat 7 ETM+c199152b2010Landsat 7 ETM+c219167

[i] Day of year (DOY) when the images were obtained is also included. The DOY of 10 cm snow depth for the different years, which was used as start of the growing season, is also given.

[ii] aDOY of 10 cm snow depth based on snow coverage by Buus-Hinkler et al. (2006).

[iii] bIn 2009, the snow depth was by far the shallowest on record and peaked at 17 cm. It was therefore below 10 cm already DOY 136 according to snow depth measurements at C1. In the central parts of the fen, it was visually seen to melt DOY 152.

[iv] cImages taken when the Scan Line Corrector on Landsat 7 was broken.

Fig. 3

Workflow for the model development and the model evaluation. The white boxes are steps in the work process of the model development or the model evaluation. The grey boxes are input data or equations going into the models. The thick arrows indicate steps in the work process, whereas thin arrows indicate input. The final results of the model evaluation were the root mean square error, the model-in situ ratio and the goodness-of-fit given by a linear regression equation.

Table 2

Monitored environmental variables used in the modelling of CH4 fluxes

YearT10WtDAL1997M1a–T19972000M2bM2M22002M1a–M1c2007M1dM1M12008M1M1M12009M1M1M12010M1–M1

[i] T 10 is the soil temperature at 10 cm depth, WtD is the water table depth and AL is the active layer thickness. Gaps in the data series were filled by linear interpolation. The ‘–’ either means that no measurements were done, or that they were not necessary in the modelling process. M1 is the monitoring site 1, M2 is the monitoring site 2 and T1997 is the Tower site 1997 (Fig. 1).

[ii] a T 10 modelled with a linear regression fitted between T 10 at monitoring site 1 d 1–57 of the growing seasons 2007, 2008 and 2009 and T 10 at C1 (R 2=0.47, n=4147).

[iii] b T 10 was measured from the 8 July 2000. At the start of the growing season, a linear regression fitted between hourly averaged T 10 at monitoring site 2 in 2000 and hourly T 10 at C1 (R 2=0.89, n=1062) was used.

[iv] cAL modelled with a linear regression fitted between AL at monitoring site 1 of the growing seasons 2007, 2008 and 2009 and AL at ZEROCALM1 (Jensen and Rasch, 2011) (R 2=0.96, n=23).

[v] d T 10 was measured from the 4 July 2007. At the start of the growing season, a linear regression fitted between hourly values of T 10 at monitoring site 1 and C1 (R 2=0.80, n=1531) for the growing season 2007, was used.

Table 3

Average (±1 SD) CH4 fluxes and environmental variables measured between 10 a.m. and 6 p.m. in the period 30 June–4 August 2007, for the different plant communities

Plant communitiesT10 (°C)WtD (cm)ALmax (cm)CH4 flux (mg CH4 m−2 h−1)Sample sizeContinuous fen7.4±1.3−3.4±3.649±39.1±5.3154Hummocky fen7.4±1.3−8.2±4.247±43.6±2.5108Grassland6.0±1.3–56±80.1±0.4110Salix snowbed8.2±2.1–78±3−0.04±0.0451Vaccinium Heath7.6±2.3–69±5−0.02±0.0454Cassiope heath7.7±1.6–74±6−0.03±0.0354Dryas heath8.9±2.1–75±5−0.03±0.0354

[i] The T 10 is the average soil temperature at 10 cm depth and WtD is the average water table depth (centimetres below moss surface) measured 21 June–4 August 2007. ALmax is the average active layer thickness (centimetres below moss surface) from the 4 August 2007, when the thickest AL was measured.

Fig. 4

The relationship between temporal variation in CH4 fluxes to (a) averaged soil temperature at 10 cm depth and (b) averaged water table depth. Equation (3) is given in the text.

Table 4

Parameters for the models relating temporal variation in CH4 fluxes and temporal variation in environmental variables

Plant communitiesEquationEnvironmental variablesabcdR2Continuous fenLinearWtD11.11±0.470.41±0.07––0.81Hummocky fenLinearWtD4.10±0.350.10±0.05––0.34Continuous fenEq. (3)T104.50±0.63–0.13±0.02–0.79Hummocky fenEq. (3)T102.14±0.45–0.10±0.04–0.47Continuous fenEq. (4)T10, AL4.41±0.59–0.13±0.020.17±0.150.76Hummocky fenEq. (4)T10, AL1.97±0.36–0.11±0.030.17±0.150.54Continuous fenEq. (5)WtD, T107.38±2.540.17±0.150.06±0.05–0.85Hummocky fenEq. (5)WtD, T102.31±0.980.01±0.060.10±0.05–0.47Continuous fenEq. (6)WtD, T10, AL7.38±2.540.17±0.150.06±0.050.17±0.150.85Hummocky fenEq. (6)WtD, T10, AL2.31±0.980.01±0.060.10±0.050.17±0.150.47

[i] Linear means a linear regression. Equations (3)–(6) are given in the text. a, b and c are fitted parameters, d was parameterised by Friborg et al. (2000), and R 2 is the coefficient of determination.

Fig. 5

Plot-averaged CH4 fluxes against spatial variation in water table depth at the DOY of the satellite image 2007 (DOY 210).

Fig. 6

Categorised water table depth (WtDcat) against Landsat-based NDWI averaged for each WtDcat category. None of the satellite pixels had an average water table above the soil surface, and there is hereby no zero WtDcat.

Fig. 7

(a) In situ and modelled CH4 flux and (b) input variables against day after day of year (DOY) of snowmelt. The in situ CH4 flux is the average±1 SD averaged for each day after DOY of snowmelt 1997, 2000, 2007 and 2008. The modelled CH4 flux is the average flux modelled by Modelsat 2 for each day after DOY of snowmelt 1997, 2000, 2007 and 2008. Modelsat 2 was chosen as it was the best model according the model evaluation. The model range is the minimum and the maximum of the eight models averaged for each day after DOY of snowmelt 1997, 2000, 2007 and 2008. The water table depth range is the minimum and maximum of the measured values for each day after DOY of snowmelt 1997, 2000, 2007 and 2008. Active layer thickness and soil temperature at 10 cm depth is the average for each day after DOY of snowmelt 1997, 2000, 2007 and 2008.

Fig. 8

Modelled CH4 fluxes against in situ CH4 fluxes. (a) Average of modelled CH4 fluxes for all Modelnosat and Modelsat to show the difference between models with and without satellite-based NDWI; (b) Modelsat 2 and Modelsat 4 against in situ CH4 fluxes to illustrate the difference between models including and excluding the temporal variation in WtD; (c) Modelsat 1 and Modelsat 2 against in situ CH4 fluxes to illustrate the difference between models including or excluding the effect of AL; and (d) Modelled CH4 fluxes modelled with Modelsat 2 for the different years against in situ CH4 fluxes.

Table 5

Ratios of modelled CH4 fluxes to in situ CH4 fluxes for the different years and the different models

ModelEquation1997200020082009Mean all yearsRMSE1nosat(3)0.881.590.831.321.16±0.361.642nosat(4)0.831.480.781.171.07±0.331.583nosat(5)1.630.851.431.31±0.402.104nosat(6)1.520.801.251.19±0.361.84Mean allnosat0.861.550.821.301.18±0.361.671sat(9_3)1.090.871.201.151.08±0.151.612sat(9_4)1.030.781.131.030.99±0.151.503sat(9_5)0.961.241.251.15±0.161.944sat(9_6)0.871.151.091.04±0.151.62Mean allsat1.060.871.181.131.07±0.141.56

[i] Root mean square errors (RMSE) in mg CH4 m−2 h−1 for the different models are also included.

Fig. 9

CH4 fluxes modelled by Modelsat 2, averaged for the Rylekærene area, and accumulated over the first 57 d of the growing seasons 1997–2010.

Fig. 10

(a) Accumulated modelled CH4 fluxes day 1–57 of the growing season for Rylekærene; (b) maximum MODIS-based NDWI for the NDWI peak period of the growing seasons in Rylekærene 1997–2010; and (c) and average soil temperature at 10 cm soil depth at C1 day 1–57 of the growing season. The gap in the soil temperature 2005 was caused by broken soil temperature sensors.

Table 6

Average (± 1 model SE) modelled CH4 fluxes for the entire Rylekærene area for the first 57 d of the growing season

YearCH4 fluxes (mg CH4 m−2 h−1)19971.5±1.220002.3±1.120022.9±3.720071.6±1.020083.0±5.320091.4±0.820101.5±0.6

[i] The model used for these estimates was the Modelsat2. The variation in CH4 fluxes due to heterogeneity in the modelled area is not included in the model SEs and it is strictly an estimate of the model uncertainty.

Table A

Abbreviations, symbols and their descriptions

Abbreviation or symbolDescriptiona, b, c and dModel parameters in Equations (3)–(6)ALActive layer thicknessALmaxPeak active layer thickness measured during the growing seasonC1Climate station (Fig. 1)DOYDay of yearFCH4Methane fluxFCH4,allAverage chamber-measured methane fluxes from all plotsFCH4,plotPlot-averaged chamber measured methane fluxesFCH4,fracFraction of CH4 flux of an individual plot in relation to the average CH4 flux from all plotskIntercept of exponential regression between FCH4,frac and WtDcat [eq. (8)]lGrowth constant of exponential regression between FCH4,frac and WtDcat [eq. (8)]M1Monitoring site 1M2Monitoring site 2ModelnosatModel data that do not include remote sensing dataModelsatModel data that do include remote sensing dataMODISModerate resolution imaging spectroradiometerNDWINormalized difference water indexNIRNear-infrared wavelengths (780–900 nm)RMSERoot mean square errorsσ2Model standard deviationσ2Standard deviation of a model parameterσ2Standard deviation of a model parameterSWIRShort-wave infrared wavelengths (1000–3000 nm)SDStandard deviationSEStandard errorT10Soil temperature at 10 cm depthT1997Tower site 1997uIntercept of linear regression between WtDcat and NDWI [eq. (2)]wSlope of linear regression between WtDcat and NDWI [eq. (2)]WtDWater table depthWtDcatCategorized water table depthyYear
DOI: https://doi.org/10.3402/tellusb.v65i0.19722 | Journal eISSN: 1600-0889
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Language: English
Page range: 19722 - 19722
Submitted on: Sep 17, 2012
Accepted on: Mar 19, 2013
Published on: Jan 1, 2013
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services
Keywords:
NDWI,
methane,
Arctic,
Landsat,
climate change

© 2013 Torbern Tagesson, Mikhail Mastepanov, Meelis Mölder, Mikkel P. Tamstorf, Lars Eklundh, Benjamin Smith, Charlotte Sigsgaard, Magnus Lund, Anna Ekberg, Julie M. Falk, Thomas Friborg, Torben R. Christensen, Lena Ström, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 65 (2013): Issue 1
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