Analysis of carbon and nitrogen dynamics in riparian soils: Model development
The quality of riparian soils and their ability to buffer contaminant releases to aquifers and streams are connected intimately to moisture content and nutrient dynamics, in particular of carbon (C) and nitrogen (N). A multi-compartment model – named the Riparian Soil Model (RSM) – was developed to help investigate the influence and importance of environmental parameters, climatic factors and management practices on soil ecosystem functioning in riparian areas. The model includes numerous improvements compared to many similar tools, in particular regarding the capability to simulate a wide range of temporal scales, from daily to centuries, along with the ability to predict the concentration and vertical distribution of dissolved organic matter (DOM). The ecological importance of DOM has been highlighted on numerous occasions, and it was found that its concentration controls the amount of soil organic matter (SOM) stored in the soil as well as the respiration rate. The moisture content was computed using a detailed water budget approach, assuming that within each time step all the water above field capacity drains to the layer underneath, until it becomes fully saturated. A mass balance approach was also used for nutrient transport, whereas the biogeochemical reaction network was developed as an extension of an existing C and N turnover model. Temperature changes across the soil profile were simulated using an existing analytical solution of the heat transport equation, assuming periodic temperature changes in the topsoil. To verify the consistency of model predictions and illustrate its capabilities, a synthetic but realistic soil profile in a deciduous forest was simulated. Model parameters were taken from the literature, and model predictions were consistent with experimental observations for a similar scenario. Modelling results stressed the importance of environmental conditions on SOM cycling in soils. The mineral and organic C and N stocks fluctuate at different time scales in response to oscillations in climatic conditions and vegetation inputs/uptake. Low frequency fluctuations with a period larger than 10 y were observed also, which were not connected to any single environmental process.
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