PT  - JOURNAL ARTICLE
AU  - D.A. Abrahamson
AU  - H.J. Causarano
AU  - J.R. Williams
AU  - M.L. Norfleet
AU  - A.J. Franzluebbers
TI  - Predicting soil organic carbon sequestration in the southeastern United States with EPIC and the soil conditioning index
AID  - 10.2489/jswc.64.2.134
DP  - 2009 Mar 01
TA  - Journal of Soil and Water Conservation
PG  - 134--144
VI  - 64
IP  - 2
4099  - http://www.jswconline.org/content/64/2/134.short
4100  - http://www.jswconline.org/content/64/2/134.full
AB  - The Soil Conditioning Index (SCI) is a relatively simple model that predicts the consequences of cropping systems and tillage practices on the status of soil organic matter in a field. The SCI is administered by the USDA Natural Resources Conservation Service to predict a positive or negative trend in soil organic matter based on knowledge of field operations, erosion loss, and organic matter inputs but has not been adequately tested against long-term management conditions that could affect soil organic carbon (SOC) dynamics. We calibrated the Environmental Policy Integrated Climate model (EPIC v. 3060) for three major land resource areas in the southeastern United States using 5 to 10 years of measured SOC data to develop a predictive relationship of SOC for 50-year simulations with SCI values. Management systems included conventional tillage and no tillage in (1) a two-year rotation of wheat (Triticum aestivum L.)/sorghum (Sorghum bicolor [L.] Moench)-corn (Zea mays L.) with low and high fertilizer application on a Blackland Prairie site in Texas, (2) a two-year rotation of corn-cotton (Gossypium hirsutum L.) with and without dairy manure application on a Coastal Plain site in Alabama, and (3) in monoculture cotton on a Mississippi Upland site. Across sites and fertilizer conditions, SOC sequestration during 50 years of using EPIC was greater under no tillage (9.5 Mg ha-1 [4.2 tn ac-1]) than under conventional tillage (6.3 Mg ha-1 [2.8 tn ac-1]) (p < 0.01). Although simulated SOC using EPIC was weakly related to SCI values, the relationship fit well within a larger dataset from the southeastern United States. The comprehensive EPIC model and the simpler SCI model could be useful tools to determine SOC storage among different management systems in the southeastern United States.