Keywords
hillslope hydrology, nutrient turnover, model coupling, ghg emissions
Start Date
1-7-2012 12:00 AM
Abstract
Biogeochemical models used for simulating greenhouse gas (GHG) emissions and nutrient leaching are mainly designed for the plot scale. Lateral fluxes of nutrients such as nitrate, which may be important drivers for soil GHG emissions, are not or only scarcely considered and explored in such models. This is due to the complexity of microbiological, physico-chemical and plant processes which need to be investigated and simulated along one spatial dimension, a column. The introduction of a second (a hillslope) or third (entire landscapes) spatial dimension is likely to introduce additional complexity which can hardly be handled by most models. However, plot scale models, validated with data obtained from plot scale studies, will systematically under- or overestimate key GHG production and consumption processes if lateral in- or efflux of nutrients to or from a given site is of significant importance. E.g. in laterally connected environments, such as riparian zones denitrification will be fuelled by lateral influx of nitrate from uphill positioned fertilized land. Thus, landscape approaches are needed to identify and realistically simulate in particular indirect GHG emissions. From our view integrated model systems can help to identify processes and ecosystem conditions in connected ecosystems across a landscape, which may also be used as a tool guiding the design of new field studies to further quantify the importance of lateral nutrient transport for soil GHG emissions.
Modelling nitrogen transport and turnover at the hillslope scale – a process oriented approach
Biogeochemical models used for simulating greenhouse gas (GHG) emissions and nutrient leaching are mainly designed for the plot scale. Lateral fluxes of nutrients such as nitrate, which may be important drivers for soil GHG emissions, are not or only scarcely considered and explored in such models. This is due to the complexity of microbiological, physico-chemical and plant processes which need to be investigated and simulated along one spatial dimension, a column. The introduction of a second (a hillslope) or third (entire landscapes) spatial dimension is likely to introduce additional complexity which can hardly be handled by most models. However, plot scale models, validated with data obtained from plot scale studies, will systematically under- or overestimate key GHG production and consumption processes if lateral in- or efflux of nutrients to or from a given site is of significant importance. E.g. in laterally connected environments, such as riparian zones denitrification will be fuelled by lateral influx of nitrate from uphill positioned fertilized land. Thus, landscape approaches are needed to identify and realistically simulate in particular indirect GHG emissions. From our view integrated model systems can help to identify processes and ecosystem conditions in connected ecosystems across a landscape, which may also be used as a tool guiding the design of new field studies to further quantify the importance of lateral nutrient transport for soil GHG emissions.
