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Soil physics meets soil biology: Towards better mechanistic prediction of greenhouse gas emissions from soil
Affiliation:1. Centre for Environment Science and Climate Resilient Agriculture, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India;2. Division of Agricultural Physics, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India;1. Institute of Hydraulics and Rural Water Management, University of Natural Resources and Life Sciences (BOKU), Muthgasse 18, 1190 Vienna, Austria;2. Austrian Agency for Health and Food Safety (AGES), Vienna, Austria;3. Institute for Soil Science, Leibniz University of Hannover, Hannover, Germany
Abstract:One of the issues hampering progress in modelling greenhouse gas (GHG) emissions from soils is a lack of co-ordination between models originating from different disciplines: soil physics and soil biology. We have reviewed recent advances in modelling both gaseous transport and the biochemical processes in the soil that lead to the emission of the main biogeneic GHGs: CO2, N2O, and CH4. The precise coupling of gaseous transport and biochemistry is necessary because CH4 and N2O can be both produced and consumed in soil, and eventual flux to the atmosphere depends on the position of reaction sites and the escape pathways for these gases. The CO2 production rate depends in turn on the efficiency of oxygen transport in the soil. Principles leading to successful simulation are: keeping a balanced level of detail in coupled model systems describing biochemical reactions and transport; reduction of unnecessary complexity by means of using the most essential relationships elucidated by comprehensive statistical model testing; consideration of all transport mechanisms in relation to prevailing ecological conditions, i.e., diffusion and convection in the air and liquid phases, plant-mediated transport and ebullition.It is important to model all three major GHG in accord with the description of O2 and N2 transport and concentration in soil. This helps: i) to estimate the full global warming potential; ii) to apply the model algorithms considering partial gas pressure and gas species interactions; iii) to describe the O2 effect on the biochemical processes in soil. We discuss the approaches linking the simple and more complex process-oriented models, and propose a strategy for up-scaling model results from soil aggregate to profile and to the field/catchment.
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