Predicting greenhouse gas emission from peat soils depending on water management with the SWAP-ANIMO model

摘要

A process-based model was developed to simulate for peat lands emission of the greenhouse gasses (GHG) CO2,CH4 and N2O,soil subsidence and nutrient loading of surface waters.The model was calibrated and validated against data from two experimental fields in the Netherlands.With the validated model scenario studies were performed to quantify the effects of water management on GHG emission,soil subsidence and nutrient loading.Raising ditchwater level was an effective measure to diminish GHG emission and subsidence.Submerged drains enhanced subsurface irrigation greatly and as a result decreased subsidence and GHG emission considerably.For nutrient loading of surface waters the optimal drain depth was around 50-60 cm below soil surface.