Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 11/12/2006
Publication Date: 11/12/2006
Citation: Causarrano, H.J., Shaw, J.N., Franzluebbers, A.J., Reeves, D.W., Balkcom, K.S., Raper, R.L., Norfleet, M.L. 2006. Epic simulation of landscape and management effects on soil organic carbon dynamics [abstract]. ASA-CSSA-SSSA Annual Meeting Abstracts. [CD-ROM] Interpretive Summary:
Technical Abstract: Simulation models integrate our understanding of soil organic C (SOC) dynamics and are useful tools for evaluating impacts of crop management on soil C sequestration. Our objectives were to calibrate the Environmental Policy Integrated Climate (EPIC) model and evaluate its performance for simulating SOC fractions, as affected by landscape and management system, in the Southeastern Coastal Plain. An automatic parameter optimization procedure was used to calibrate the model against results from a site-specific experiment in central Alabama. Model performance in predicting corn (Zea mays L.) and cotton (Gossypium hirsutum L.) yields and SOC dynamics was evaluated on different Coastal Plain soil landscapes (Typic, Oxyaquic and Aquic Paleudults) during the initial years of conservation tillage adoption (5 years). Simulated yield explained 88% of measured yield variation, with the best agreement in the drainageway and the least on the sideslopes. Simulation of SOC fractions explained 7, 27 and 41% of the total variation in the data for microbial biomass C (MBC), slow humus C (SHC) and total organic C (TOC), respectively. Lowest errors on TOC simulations (0-20 cm) were found on the sideslope and in the drainageway. We concluded that the automatic parameterization was successful, although further work is needed for the SHC and MBC fractions, and to improve EPIC predictions of SOC dynamics with depth. Overall, EPIC was sensitive to spatial patterns that resulted from different soil landscapes. Our results show that proper parameterization is essential with EPIC before it can be used as a tool for simulating field-scale SOC dynamics impacted by short-term management.