Tuesday, 11 July 2006 - 11:15 AM
36-5

The GEFSOC Modeling System, A Processed-Based Modeling Approach for Spatially Explicit Estimates of Soil Organic Carbon Stock Change.

E. Milne1, Mark Easter1, Keith Paustian1, Rida Al-Adamat2, Tapas Bhattacharyya3, Carlos E.P. Cerri4, Peter Kamoni5, Carlos C. Cerri4, Niels Batjes6, Martial Bernoux7, Kevin Coleman8, Pete Falloon9, Christian Feller7, Patrick Gicheru10, Kendrick Killian1, Dilipkumar Pal3, David Powlson11, Zahir Rawajfih12, and Mohamed Sessay13. (1) The Department of Crop and Soil Sciences, Colorado State University, Fort Collins, CO 80523-1170, (2) The Badia Research and Development Programme, Nifeh, Mafraq, 25454, Jordan, (3) National Bureau of Soil Survey and Land Use Planning, Amravati Road, Nagpur, 440010, India, (4) Centro de Energia Nuclear na Agricultura, Avenida Centenario 303, Sao Dimas, Piracicaba, Brazil, (5) Kenya National Agricultural Research Laboratory, PO Box 14733, Nairobi, 14733, Kenya, (6) ISRIC-World Soil Information, AJ Wageningen, 35-, 6700, Netherlands, (7) IRD, BP 64501, Montpellier, France, (8) Rothamsted Research, Agriculture and Environment Division, Harpenden, AL52JQ, United Kingdom, (9) The Met Office, Hadley Centre for Climate Prediction and Research, Fitzroy Road, Exeter, EXi3PB, United Kingdom, (10) Kenya Soil Survey, NARL, PO Box 14733, Nairobi, Kenya, (11) Rotahmsted Research , Agriculture and Environment Division, Harpenden, AL52JQ, United Kingdom, (12) Jordan University of Science and Technology, PO Box 3030, 22110, Irbid, Jordan, (13) UNEP, United Nations Avenue, Gigiri, Nairobi, Kenya

The Kyoto Protocol and the United Nations conventions on climate change, desertification and biodiversity all recognize the importance of Soil Organic Carbon (SOC) and point to the need for quantification of SOC stocks and changes. SOC levels are related to atmospheric C levels with soils having the potential for C release or sequestration, depending on land use and management. In addition SOC plays a vital role in ecosystem function, determining soil fertility, water holding capacity and susceptibility to land degradation. Several studies have considered SOC stocks at the plot scale, however these are site specific and of limited value in making inferences about larger areas. An understanding of SOC stocks and changes at the national and regional scale is necessary in order to further our understanding of the global carbon cycle, to assess the responses of terrestrial ecosystems to climate change and to aid policy makers in making land use/management decisions. In order to gain such an understanding a system is needed that can deal with complex combinations of environmental variables. Process based modelling approaches are designed to deal with such complexities. They also allow estimates to be made in a manner that accounts for the underlying processes leading to SOC change. Ecosystem models, designed for site scale applications can be linked to spatial data bases giving spatially explicit results that allow geographic areas of change in SOC stocks to be identified. Some studies have used variations on this approach to estimate SOC stock changes at the sub-national and national scale for areas of the USA and Europe and at the watershed scale for areas of Mexico and Cuba. However, a need remained for a national and regional scale spatially-explicit model-based system that is generically applicable, encompassing as wide a range of soil types, climates and land uses as possible. The Global Environment Facility Soil Organic Carbon (GEFSOC) Modeling System has been developed in response to this need. The system links two process based models (RothC and Century) and an empirical method (The IPCC Method) to spatially explicit data through a geographical information system. The system uses these methods to make spatially explicit estimates of SOC stocks and stock changes under land management and climate change scenarios for given geographic areas. The development of the system is discussed and a comparison of results from 4 case study areas (The Brazilian Amazon, Kenya, Jordan and The Indian Indo-Gangetic Plains) is given. Finally potential future uses of The GEFSOC System are considered including the scope to allow comparable estimates of SOC stocks and changes to be made for diverse conditions and the opportunities to provide information for countries wishing to take part in an emerging carbon market. Keywords: Soil organic carbon, models, spatial data, complex systems, GEFSOC modelling system.


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