Determination of carbon sequestration potential in different land uses of Kermanshah province using intelligent data mining systems

Soil organic matter (SOM) is a key element in soil productivity and atmospheric carbon sequestration is sustainable approach for climate change mitigation. This research was conducted to determine the main factor controlling SOM in different land use, especially agricultural lands and evaluation the carbon sequestration potential in the Kermanshah province. For this means, artificial neural networks and decision tree was applied. For determining priority effects of physical and management factors sensitivity analysis was done. Results indicated that in agricultural lands, management related factors including, tillage related scenarios and straw management system dominantly controlled SOM contents. In rangelands and forest, by physical and management factors had equal effects on SOM variability. Analysis of the results indicated that by modifying tillage related factors especially avoid of moldboard plow and optimize straw management in agricultural lands, grazing control in rangelands and avoid deforestation in forests of the province, 30 8.2 and 7.1 million ton atmospheric carbon could be sequestered across the mentioned land uses.