 |
| Titel |
Improving a plot-scale methane emission model and its performance at a northeastern Siberian tundra site |
| VerfasserIn |
Y. Mi, J. van Huissteden, F. J. W. Parmentier, A. Gallagher, A. Budishchev, C. T. Berridge, A. J. Dolman |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1726-4170
|
| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 11, no. 14 ; Nr. 11, no. 14 (2014-07-30), S.3985-3999 |
| Datensatznummer |
250117529
|
| Publikation (Nr.) |
 copernicus.org/bg-11-3985-2014.pdf |
|
|
|
|
|
| Zusammenfassung |
In order to better address the feedbacks between climate and wetland methane
(CH4) emissions, we tested several mechanistic improvements to the wetland
CH4 emission model Peatland-VU with a longer Arctic data set than any other
model: (1) inclusion of an improved hydrological module, (2) incorporation of
a gross primary productivity (GPP) module, and (3) a more realistic soil-freezing
scheme.
A long time series of field measurements (2003–2010) from a tundra site in
northeastern Siberia is used to validate the model, and the generalized
likelihood uncertainty estimation (GLUE) methodology is used to test the
sensitivity of model parameters.
Peatland-VU is able to capture both the annual magnitude and seasonal
variations of the CH4 flux, water table position, and soil thermal
properties. However, detailed daily variations are difficult to evaluate due
to data limitation. Improvements due to the inclusion of a GPP module are
less than anticipated, although this component is likely to become more
important at larger spatial scales because the module can accommodate the
variations in vegetation traits better than at plot scale.
Sensitivity experiments suggest that the methane production rate factor, the
methane plant oxidation parameter, the reference temperature for temperature-dependent
decomposition, and the methane plant transport rate factor are the
most important parameters affecting the data fit, regardless of vegetation
type. Both wet and dry vegetation cover are sensitive to the minimum water
table level; the former is also sensitive to the runoff threshold and open water correction
factor, and the latter to the subsurface water evaporation and evapotranspiration correction
factors.
These results shed light on model parameterization and future improvement of
CH4 modelling. However, high spatial variability of CH4 emissions
within similar vegetation/soil units and data quality prove to impose severe
limits on model testing and improvement. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|