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United States Department of Agriculture

Agricultural Research Service

The CQESTR Model

CQESTR version 2.0

Soil carbon (C) models are useful for examining the complex interactions between climate, crop, and soil management practices and their influences on long-term changes in soil organic matter (SOM) or soil organic carbon (SOC). The C model CQESTR, pronounced 'sequester', has been developed by USDA-ARS scientists at the Columbia Plateau Conservation Research Center, Pendleton, Oregon, USA. The CQESTR model was developed to evaluate the effect of agricultural management practices on short- and long-term SOM dynamics.

Description of CQESTR:

The CQESTR model (v. 2.0) is a process-based soil C balance model that computes biological decomposition rates of crop residue or organic amendments as they convert to soil organic matter (SOM) or SOC. The model is used for the field scale evaluation of SOC stocks (Gollany et al., 2010, 2012; Liang et al., 2009, 2008; Rickman et al., 2002). The model operates on a daily time-step and performs long-term (100-yr) simulations. The C pools are depicted as a continuum. The basic model structure and C flow in the CQESTR model is illustrated in Fig. 1. The organic material decomposition is a three phase process. After each residue placement in the soil, decomposition occurs in two phases. Phase I, is a rapid phase covering the first 1000 cumulative degree-days (CDD or thermal time), approximating the oxidation of readily metabolizable substrate. Phase II, is a slow decomposition phase, representing oxidization of more recalcitrant materials. Crop residues and organic amendments are categorized by their placement in the soil and their identities are maintained during the two phase decomposition. Each organic residue addition is tracked separately according to its placement within distinct soil horizons. After 15,000 CDD when Phase II is complete, the composted residue is transferred to the stable SOM pool (Phase III).

Schematic of carbon flow in the CQESTR model
Fig. 1. Schematic of Carbon flow in the CQESTR model.

Decomposition model used is as follows:

Decomposition model for residue

Computation of stable SOM at each time-step in each soil layer is as follows:

SOM remaining

The CQESTR Model: SOC Budget Algorithms

The CQESTR model (v. 2.0) is a process-based soil C balance model. The total soil organic C budget can be represented by Eq. [1], using units of dry weight per unit area within each soil layer.

Where: TOC = Total SOC; CSOM = C in the stable SOM; CDOM = Decomposed organic matter lost as C dioxide (CO2); CS, l = C in shoot residue l; CDS, l = C lost as CO2 from decomposed shoot residue l; CR, m = C in root residue m; CDR, m = C lost as CO2 from decomposed root residue m; CA, n = C in organic amendment n; CDA, n = C lost as CO2 from decomposed amendment n; u, v, w = All applications of organic materials from the initial time to the current day.


The CQESTR model uses readily available input data at the field scale. Data inputs include weather, above-ground and below-ground biomass additions, N content of residues and amendments, soil properties, and management factors such as tillage and crop rotation. Crop rotation, annual yields, and tillage information are organized in crop management files associated with the c-factor of the Revised Universal Soil Loss Equation (RUSLE, version 1) (Renard et al., 1996). These consist of crop grain yields, shoot-to-grain ratios, dates of all operations (e.g., tillage, seeding, harvest, biomass addition, biomass removal, etc.), depth of tillage and the fraction of the soil surface covered, and effects of tillage on residue (e.g. fraction of pre-tillage residue weight remaining on the soil surface after each tillage). Crop rotation, grain and residue, residue removal and tillage information are required explicitly. Residue consumption by macro-fauna, deposition or loss of SOC at the soil surface, or the physical transfer between soil layers, are not accounted for in the CQESTR model.

Calibration: The model was calibrated using information from six long-term experiments across North America (Breton, AB, 60 yrs; Columbia, MO, >100 yrs; Florence, SC, 19 yrs; Hoytville, OH, 31 yrs; Lincoln, NE, 26 yrs; and Pendleton, OR, 76 yrs) having a range of soil properties and climate (Fig.2).

Long-term CQESTR Experiment sites across North America
Fig. 2. Long-term Experiment sites across North America used in calibration and validation of CQESTR.

Validation: The CQESTR model was validated using data from several additional long-term experiments (8 – 106 yrs) across North America having a range of SOM (4.2 – 33.6 g SOC/kg). Regression analysis of 306 pairs of predicted and measured SOM data under diverse climate, soil texture and drainage classes, and agronomic practices at 13 agricultural sites resulted in a linear relationship with an r2 of 0.95 (P < 0.0001) and a 95% confidence interval of 2.5 g SOC/kg (Fig. 3). The CQESTR model can be used to predict and evaluate soil organic matter or soil organic carbon changes from various agricultural management practices (Gollany et al., 2012; Leite et al., 2009; Plaza et al., 2012) including residue removal for biofuel (Gollany et al., 2011; Wilhelm et al., 2010), and climate change scenarios (Gollany and Polumsky, 2014).

Comparison of observed soil organic matter contents shown on graph
Fig. 3. Comparison of observed soil organic matter contents of 13 long-term sites across North America used for validating CQESTR.


Gollany, H.T., Polumsky, R.W. 2014. Measured and CQESTR Simulated Soil Organic Carbon Changes of Dryland Agroecosystem Under Climate Change Scenarios. 54-10. Special Sessions: Symposium--Climate Change Impacts on Soil Carbon: Understanding and Estimating the Extent and Rates of Reactions, Processes, Interactions and Feedbacks. ASA CSSA SSSA 2014 International Annual Meetings. Nov. 2-5, 2014. Long Beach, CA

Gollany, H.T., R.F. Follett, and Y. Liang. 2012. CQESTR Simulations of Soil Organic Carbon Dynamics. In Liebig M. A., A. J. Franzluebbers, R. F. Follett (eds.), Managing Agricultural Greenhouse Gases: Coordinated Agricultural Research Through GRACEnet to Address our Changing Climate, Academic Press, San Diego, CA. p. 271- 292.

César Plaza, Hero Gollany, Guido Baldoni , Alfredo Polo, Claudio Ciavatta. 2012. Predicting Long-term Organic Carbon Dynamics in Organically-amended Soils Using the CQESTR Model. J. Soil Sed. 477:486-493.

Gollany, H.T., A. Fortuna, M. Samuel, F.L. Young, W. Pan, and M. Pecharko. 2012. Estimating soil organic carbon accretion vs. sequestration using chemical and physical fractionation and the CQESTR model. Soil Sci. Soc. Am. J. 76: 618 –629.

Gollany, H.T., R.W. Rickman, Y. Liang, S.L. Albrecht, S. Machado, S. Kang. 2011. Predicting Agricultural Management Influence on Long-Term Soil Organic Carbon Dynamics: Implications for Biofuel Production. Agron. J.103:234-246.

Gollany, H. T., J. M. Novak, Y. Liang, S. L. Albrecht, R. W. Rickman, R. F. Follett, W. W. Wilhelm, and P. G. Hunt. 2010. Simulating soil organic carbon dynamics with residue removal using the CQESTR Model. Soil Sci. Soc. Am. J. 74:372-383.

Wilhelm, W.W., J.R. Hess, D.L. Karlen, J.M.F. Johnson, D.J. Muth, J.M. Baker, H.T. Gollany, J.M. Novak, D.E. Stott, and G.E. Varvel. 2010. Balancing Limiting Factors and Economic Drivers for Sustainable Midwestern US Agricultural Residue Feedstock Supplies. Indus. Biotech. 6:271-287.

Leite, L.F.C., P.C. Doraiswamy, H.J. Causarano, H.T. Gollany, S. Milak, E.S. Mendonca. 2009. Modeling organic carbon dynamics under no-tillage and plowed systems in tropical soils of Brazil using CQESTR. Soil and Tillage Res. 102:118-125.

Liang, Y, H.T. Gollany, R.W. Rickman, S.L. Albrecht, R.F. Follett, W.W. Wilhelm, J. M. Novak, and C.L. Douglas, Jr. 2009. Simulating soil organic matter with CQESTR (v. 2.0): Model description and validation against long-term experiments across North America. Ecol. Model. 220:568-581.

Liang, Y, H.T. Gollany, R.W. Rickman, S.L. Albrecht, R.F. Follett, W.W. Wilhelm, J. M. Novak, and C.L. Douglas, Jr. 2008. CQESTR simulation of management practice effects on long-term soil organic carbon. Soil Sci. Soc. Am. J. 72:1486-1492.

Renard, K.G., G.R. Foster, G.A. Weesies, D.K. McCool, and D.C. Yoder (Coord.). 1996. Predicting Soil Erosion by Water: A guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). U.S. Department of Agriculture, Agriculture Handbook No. 703. U.S. Gov. Print Office, Washington D.C.

Rickman, R., C. Douglas, S. Albrecht, and J. Berc. 2002. Tillage, crop rotation, and organic amendment effect on changes in soil organic matter. Environ. Pollut. 116:405-411.

Last Modified: 1/20/2015
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