Advanced

Modelling methane emissions from Arctic tundra wetlands : effects of fractional wetland maps

Cai, Zhanzhang LU (2014) In Student thesis series INES NGEM01 20132
Dept of Physical Geography and Ecosystem Science
Abstract
The Arctic tundra has been considered as one of the most sensitive areas to global climate change. One impact of global warming is that permafrost thawing could result in more waterlogged and anaerobic conditions, and consequently an increasing release of methane (CH4) to the atmosphere. These potential CH4 emissions can further amplify global warming. Therefore, it is important to assess the quantity of CH4 emissions from Arctic tundra wetlands and their sensitivity to climate change. Process-based CH4 modelling is commonly used to estimate CH4 emissions using single-source fractional wetland maps; however, it is not clear how the difference among multisource of fractional wetland maps affects CH4 estimations. In this study LPJ-GUESS... (More)
The Arctic tundra has been considered as one of the most sensitive areas to global climate change. One impact of global warming is that permafrost thawing could result in more waterlogged and anaerobic conditions, and consequently an increasing release of methane (CH4) to the atmosphere. These potential CH4 emissions can further amplify global warming. Therefore, it is important to assess the quantity of CH4 emissions from Arctic tundra wetlands and their sensitivity to climate change. Process-based CH4 modelling is commonly used to estimate CH4 emissions using single-source fractional wetland maps; however, it is not clear how the difference among multisource of fractional wetland maps affects CH4 estimations. In this study LPJ-GUESS WHyMe was applied to simulate CH4 emissions of Arctic tundra between 1961 and 2009 by using multisource fractional wetland maps, and their quantitative and qualitative differences in estimating CH4 emissions from these fractional wetland maps was compared. Parameter sensitivity tests and a parameter optimization for the model were performed before the model was applied to Arctic tundra. The CH4/CO2 production ratio under anaerobic conditions (CH4/CO2) and fraction of available oxygen used for methane oxidation (foxid) were identified as the most important model parameters in estimating total CH4 fluxes of Arctic tundra in the period 1961-2009. The regional simulation using multisource fractional wetland maps showed that the uncertainties of CH4 emissions in Arctic tundra caused by fractional wetland maps were larger than that due to parameter uncertainty. However, the temporal variability of CH4 emissions in Arctic tundra is not significantly different when using different fractional wetland maps. For different transport pathways of CH4 emissions, diffusion was determined as the dominant pathway for methane transport from wetland to the atmosphere in Arctic tundra. CH4 fluxes in Arctic tundra are more sensitive to soil temperature at 25 cm if the water table position is above the soil surface. (Less)
Please use this url to cite or link to this publication:
author
Cai, Zhanzhang LU
supervisor
organization
course
NGEM01 20132
year
type
H2 - Master's Degree (Two Years)
subject
keywords
fractional wetland maps, Arctic tundra, methane emissions, biogeochemical modelling, Physical Geography and Ecosystem analysis, LPJ-GUESS, sensitivity test, parameter optimization
publication/series
Student thesis series INES
report number
306
language
English
id
4392846
date added to LUP
2014-04-14 09:26:49
date last changed
2014-04-14 09:26:49
@misc{4392846,
  abstract     = {The Arctic tundra has been considered as one of the most sensitive areas to global climate change. One impact of global warming is that permafrost thawing could result in more waterlogged and anaerobic conditions, and consequently an increasing release of methane (CH4) to the atmosphere. These potential CH4 emissions can further amplify global warming. Therefore, it is important to assess the quantity of CH4 emissions from Arctic tundra wetlands and their sensitivity to climate change. Process-based CH4 modelling is commonly used to estimate CH4 emissions using single-source fractional wetland maps; however, it is not clear how the difference among multisource of fractional wetland maps affects CH4 estimations. In this study LPJ-GUESS WHyMe was applied to simulate CH4 emissions of Arctic tundra between 1961 and 2009 by using multisource fractional wetland maps, and their quantitative and qualitative differences in estimating CH4 emissions from these fractional wetland maps was compared. Parameter sensitivity tests and a parameter optimization for the model were performed before the model was applied to Arctic tundra. The CH4/CO2 production ratio under anaerobic conditions (CH4/CO2) and fraction of available oxygen used for methane oxidation (foxid) were identified as the most important model parameters in estimating total CH4 fluxes of Arctic tundra in the period 1961-2009. The regional simulation using multisource fractional wetland maps showed that the uncertainties of CH4 emissions in Arctic tundra caused by fractional wetland maps were larger than that due to parameter uncertainty. However, the temporal variability of CH4 emissions in Arctic tundra is not significantly different when using different fractional wetland maps. For different transport pathways of CH4 emissions, diffusion was determined as the dominant pathway for methane transport from wetland to the atmosphere in Arctic tundra. CH4 fluxes in Arctic tundra are more sensitive to soil temperature at 25 cm if the water table position is above the soil surface.},
  author       = {Cai, Zhanzhang},
  keyword      = {fractional wetland maps,Arctic tundra,methane emissions,biogeochemical modelling,Physical Geography and Ecosystem analysis,LPJ-GUESS,sensitivity test,parameter optimization},
  language     = {eng},
  note         = {Student Paper},
  series       = {Student thesis series INES},
  title        = {Modelling methane emissions from Arctic tundra wetlands : effects of fractional wetland maps},
  year         = {2014},
}