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Integration of the DAYCENT Biogeochemical Model within a Multi-Model Framework

This paper was presented at the 2012 International Congress on Environmental Modelling and Software in Leipzig, Germany on July 15, 2012.

Abstract: Agricultural residues are the largest near term source of cellulosic biomass for bioenergy production, but removing agricultural residues sustainably requires considering the critical roles that residues play in the agronomic system. Determination of sustainable removal rates for agricultural residues has received significant attention and integrated modeling strategies have been built to evaluate sustainable removal rates considering soil erosion and organic matter constraints. However, the current integrated model, comprised of the agronomic models WEPS, RUSLE2, and SCI, does not quantitatively assess the impacts of residue removal on soil organic carbon and long term crop yields. Furthermore, it does not evaluate the impact of residue removal on greenhouse gas emissions, specifically N2O and CO2 gas fluxes from the soil surface. The DAYCENT model simulates several important processes for determining agroecosystem performance. These processes include daily nitrogen gas flux, daily CO2 flux from soil respiration, soil organic carbon and nitrogen, net primary productivity, and daily water and nitrate leaching. Each of these processes is an indicator of sustainability when evaluating emerging cellulosic biomass production systems for bioenergy. This paper couples the DAYCENT model with the existing integrated model to investigate additional environment al impacts of agricultural residue removal. The integrated model is extended to facilitate two - way coupling between DAYC ENT and the existing framework. The extended integrated model, including DAYCENT, is applied to investigate additional environmental impacts from a recent sustainable agricultural residue removal dataset. Results show some differences in sustainable removal rates compared to previous results for a case study county in Iowa , US . The extended integrated model also predict s that long term yields will decrease .32% – 1.43 % under sustainable residue removal management practices.

Jared Abodeely , David Muth , Kenneth Mark Bryden
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