Integration of the DAYCENT Biogeochemical Model within a Multi-Model Framework [electronic resource]

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Tác giả:

Ngôn ngữ: eng

Ký hiệu phân loại: 333.785 Economics of land and energy

Thông tin xuất bản: Idaho Falls, Idaho : Oak Ridge, Tenn. : Idaho National Laboratory ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2012

Mô tả vật lý: Medium: ED : , digital, PDF file.

Bộ sưu tập: Metadata

ID: 265271

Agricultural residues are the largest near term source of cellulosic 13 biomass for bioenergy production, but removing agricultural residues sustainably 14 requires considering the critical roles that residues play in the agronomic system. 15 Determining sustainable removal rates for agricultural residues has received 16 significant attention and integrated modeling strategies have been built to evaluate 17 sustainable removal rates considering soil erosion and organic matter constraints. 18 However the current integrated model does not quantitatively assess soil carbon 19 and long term crop yields impacts of residue removal. Furthermore the current 20 integrated model does not evaluate the greenhouse gas impacts of residue 21 removal, specifically N2O and CO2 gas fluxes from the soil surface. The DAYCENT 22 model simulates several important processes for determining agroecosystem 23 performance. These processes include daily Nitrogen-gas flux, daily carbon dioxide 24 flux from soil respiration, soil organic carbon and nitrogen, net primary productivity, 25 and daily water and nitrate leaching. Each of these processes is an indicator of 26 sustainability when evaluating emerging cellulosic biomass production systems for 27 bioenergy. A potentially vulnerable cellulosic biomass resource is agricultural 28 residues. This paper presents the integration of the DAYCENT model with the 29 existing integration framework modeling tool to investigate additional environment 30 impacts of agricultural residue removal. The integrated model is extended to 31 facilitate two-way coupling between DAYCENT and the existing framework. The 32 extended integrated model is applied to investigate additional environmental 33 impacts from a recent sustainable agricultural residue removal dataset. The 34 integrated model with DAYCENT finds some differences in sustainable removal 35 rates compared to previous results for a case study county in Iowa. The extended 36 integrated model with DAYCENT also predicts that long term yields will decrease.
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