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United States Department of Agriculture

Agricultural Research Service

Research Project: Improved Soil Managment Practices for Tilled Summer Fallow in the Pacific Northwest

Location: Soil and Water Conservation Research

Title: Simulating soil organic carbon changes across toposequences under dryland agriculture using CQESTR

Author
item Gollany, Hero
item Elnaggar, Abdelhamid

Submitted to: Ecological Modelling
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/27/2017
Publication Date: 4/24/2017
Citation: Gollany, H.T., Elnaggar, A.A. 2017. Simulating soil organic carbon changes across toposequences under dryland agriculture using CQESTR. Ecological Modelling. 355:97-104.

Interpretive Summary: Soil organic carbon (SOC) and its management under dryland cropping systems are very critical for both crop productivity and environment health. The objective of this study was to evaluate the performance of CQESTR (pronounced sequester), a process-based C model, in simulating soil organic carbon changes across toposequences of selected fields and agriculture management practices along a precipitation gradient in a dryland region of Oregon, USA. Soil samples were collected from five landscape positions (summit, shoulder, backslope, footslope, and toeslope) during early 1980s and early 2000s. Simulation scenarios were developed based on field management practices, crop rotations, soil properties, and climatic data. CQESTR simulated results were compared with the measured soil organic carbon from each landscape position and for all the sampling locations. Significant correlations were found between the measured and the simulated soil organic carbon at summit, shoulder, backslope, footslope, and toeslope. The smallest correlation value at backslope could be from soil deposition due to erosion. No significant changes in soil organic carbon were found between summit, shoulder, backslope, and footslope; however, toeslope had the highest soil organic carbon (1.08 %). CQESTR successfully simulated soil organic carbon at most of the studied sites and landscape positions, except at toeslope for a location with high annual deposition of C-rich soil eroded from the upper landscape position. The results were supported by a low mean square deviation between the measured and the simulated soil organic carbon. Deposition or loss of carbon by wind or water erosion was not accounted for because of lack of soil erosion algorithms in CQESTR. [GRACEnet and REAP publication].

Technical Abstract: Soil organic carbon (SOC) and its management under dryland cropping systems are very critical for both crop productivity and environment health. The objective of this study was to evaluate the performance of CQESTR, a process-based C model, in simulating SOC changes across toposequences of selected fields and agriculture management practices along a precipitation gradient in a dryland region of Oregon, USA. Geo-referenced soil samples were collected from summit (SU), shoulder (SH), backslope (BS), footslope (FS), and toeslope (TS) positions during early 1980s and early 2000s. Simulation scenarios were developed based on field management practices, crop rotations, soil properties, and climatic data. CQESTR simulated results were compared with the measured SOC from each landscape position. Significant (P <0.0001) correlations (r= 0.93) were found between the measured and the simulated SOC at SU, SH (r= 0.91), BS (r= 0.83), FS (r= 0.89), and TS (r= 0.89). The smallest correlation value at BS could be from soil deposition due to erosion. No significant changes in SOC were found between SU, SH, BS, and FS landscape positions; however, TS had the highest SOC (10.8 ±5.8 g C kg-1). CQESTR successfully simulated SOC at most of the studied sites and landscape positions, except at TS for a location with high annual deposition of C-rich soil eroded from the upper landscape position. CQESTR could be used to predict SOC changes across toposequence and at the landscape scale level with reasonable accuracy. The results were supported by a linear relation with an r^2 of 0.89 and a low mean square deviation (MSD= 0.24) between the measured and the simulated SOC [GRACEnet and REAP publication].

Last Modified: 09/24/2017
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