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Major results

  • At first we tried to establish a very simplistic parameterization technique for present day wetlands modeling. The idea is to extend the scheme for data strived past climatic scenarios, once it is validated for present day. In achieving this, we used soil wetness parameter from dynamic vegetation model CARAIB (Otto et al.2002, Laurent et al.2008) along with terrain elevation gradient from GTOPO 30 to identify potential wetlands at present day. In this method, two sets of threshold values for soil wetness are chosen separately for northern latitudes (30°N-90°N) and for the rest of globe at flat areas (slope gradient < .3) to locate the wetlands. The result is validated with wetland areas from the GLWD database (Lehner et al.2004) over different regions.

  GLWD database (area in million km^2) Modeled wetlands (area in million km^2)
Total area of wetlands 9.10 10.87
Canada 1.60 1.92
Alaska 0.45 0.11
North America 2.86 3.17
South America 1.59 1.55
Europe 0.26 1.52
Africa 1.31 1.33
Asia 2.90 2.97


  • It is evident from the table that in our model global wetlands are over estimated by 1.7 mill. km^2. Although some of the wetlands are missing over Alaskan region, Europe is having more compared to GLWD. Otherwise, over the continents of Asia, Africa and south America, model estimation is close to the GLWD database.

  • Climatological soil wetness provided by CARAIB enables us to study the wetlands seasonality and its contribution to annual methane emission. In fact global wetlands show strong seasonality in their areal extent due to climatic forcing and these factors differ from northern latitude  to tropics and sub-tropics. As a whole, wetlands vary from a maximum area of 15 mill. km^2 to to a minimum of 5 mill. km^2 annualy. The following figures describe seasonal pattern of wetland extent separately for northern latitudes (30°N-90°N) and tropics (40°S-20°N) over a climatological year.


The figure shows that over northern latitude, wetlands show strong seasonality and at summer expands 2 to 3 times compared to winter. However, over tropics it does not exhibit such a clear trend and shows a dip from April to July only to increase again.


  • The next aspect of our work is focused wetland emissions on a global scale. Methane emission from wetlands depends majorly on soil temperature and soil organic availability. In this present study we followed the emission parameterization method as adapted by Gedney et al. 2004 to prepare monthly global wetland methane emission maps. In fact, this topic has not received much attention in the literature up to now, but a few case studies and global inventories exist which try to establish a seasonal cycle of wetland occurrence and methane emissions (Aslemann and Crutzen 1989, Whalen and Reeburgh 1992, Milaon et al. 2005). According to these studies, the global wetland methane emissions are about a factor of 2 to 3 higher during June to September compared to the rest of the year. Apart from the seasonality of inundation, the other factors contributing to emission is the trend in soil temperature and the geographical distribution of soil organic matters. However it is to be noted that the seasonal cycle of methane emissions is not directly proportional to the seasonal wetland extent, because methane emissions depend non-linearly on soil temperature. Due to a strong temperature trend, methane emission from Northern wetlands is majorly affected by it. However, at tropical regions temperature does not vary much over the year and here the emission trend is mainly governed by wetland seasonality. From this model study it is found that wetland contributes to approximately 350 Tg methane per year to the atmosphere The figure below represents the climatological average map of global wetland methane emission rate.


Global wetland methane emission rate (gm m^-2 sec^-1).

  • At present the wetland methane emission scheme as described, has been used interactively within the ECHAM chemistry climate model for present day methane simulation. Efforts are going on for Wetland modeling at LGM and subsequent climate simulation.




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