C-Farm: A simple model to evaluate the carbon balance of soil profiles

Kemanian, Armen R.; Stöckle, Claudio O.

doi:10.1016/j.eja.2009.08.003

Cited by 59 publications

(53 citation statements)

References 32 publications

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“…The lower SDR values are associated with operations that gently disturb the soil, and the higher SDRs (25 to 30) are associated with operations with greater soil disturbance, such as offset disking and moldboard plowing that aggressively break up soil aggregates and physically mix the soil. For each soil layer affected by a tillage operation, the cumulative SDR increases with each operation and decreases as a function of time and soil water content at a rate ~2% per day for a soil at field capacity (Kemanian and Stöckle 2010). The SDR and the soil clay concentration or fraction are used to determine a tillage adjustment factor (F t > 1) that multiplies the SOC oxidation rate of all SOC pools in the layer.…”

Section: Residuesmentioning

confidence: 99%

“…Emissions of N 2 O due to nitrification are modeled as a fraction of nitrified N determined by a function of soil moisture and temperature (Maag and Vinther 1996). The effect of tillage was calculated based on soil disturbance ratings (SDR) used by the US Department of Agriculture Natural Resource Conservation Service (USDA NRCS 2002) to characterize a large number of field operations, including mechanical operations other than tillage (Kemanian and Stöckle 2010). Each operation is given a rating from 0 to 30.…”

Section: Residuesmentioning

confidence: 99%

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Carbon storage and nitrous oxide emissions of cropping systems in eastern Washington: A simulation study

Stöckle¹,

Higgins²,

Kemanian³

et al. 2012

Journal of Soil and Water Conservation

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Conservation tillage is an agricultural strategy to mitigate atmospheric greenhouse gas (GHG) emissions. In eastern Washington, we evaluated the long-term effects of conventional tillage (CT), reduced tillage (RT) and no-tillage (NT) on soil organic carbon (SOC) storage and nitrous oxide (N 2 O) emissions at three dryland and one irrigated location using the cropping systems simulation model CropSyst. Conversion of CT to NT produced the largest relative increase in SOC storage (ΔSOC, average yearly change relative to CT) in the top 30 cm (11.8 in) of soil where ΔSOC ranged from 0.29 to 0.53 Mg CO 2 e ha -1 y -1 (CO 2 e is carbon dioxide [CO 2 ] equivalent of SOC; 0.13 to 0.24 tn CO 2 e ac -1 yr -1). The ΔSOC were less with lower annual precipitation, greater fallow frequency, and when changing from CT to RT. Overall, ΔSOC decreased from the first to the third decade after conversion from CT to NT or RT. Simulations of ΔSOC for the conversion of CT to NT based on a 0 to 15 cm (0 to 5.9 in) soil depth were greater than the ΔSOC based on a 0 to 30 cm depth, primarily due to differences among tillage regimes in the depth-distribution of carbon (C) inputs and the resultant SOC distribution with depth. Soil erosion rates under CT in the study region are high, posing deleterious effects on soil quality, productivity, and aquatic systems. However, an analysis that includes deposition, burial, and sedimentation on terrestrial and aquatic systems of eroded SOC indicates that the substantial erosion reduction obtained with RT and NT may result only in minor additional SOC oxidation as compared to CT. Simulated N 2 O emissions, expressed as CO 2 equivalent, were not very different under CT, RT, and NT. However, N 2 O emissions were sufficiently high to offset gains in SOC from the conversion of CT to RT or NT. Thus, reducing tillage intensity can result in net C storage, but mitigation of GHG is limited unless it is coupled with nitrogen (N) fertilizer management to also reduce N 2 O emission. . Tillage operations that mix crop residues with soil and decrease soil aggregation facilitate microbial degradation of soil organic matter (Balesdent et al. 2000;Six et al. 2004a). Therefore, a shift from high physical disturbance conventional tillage (CT) to reduced tillage (RT) to no-tillage (NT) can increase SOC storage (Allmaras et al. 2000;Huggins et al. 2007). Crop rotations that increase carbon (C) inputs from roots and residues can also increase the storage of SOC (Huggins et al. 1998;Huggins et al. 2007).In addition to SOC storage, reduction of nitrous oxide (N 2 O) emissions also contributes to mitigate the climate impact of agriculture. According to the US Environmental Protection Agency (2011), agriculture contributes 7.4% of total greenhouse gas (GHG) emissions in the United States, with approximately 70% due to N 2 O production from agricultural soil management (e.g., nitrogen [N] fertilizer). Crop management and N fertilization strategies that limit the availability of mineral N for N 2 O production can he...

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Section: Residuesmentioning

confidence: 99%

Section: Residuesmentioning

confidence: 99%

Carbon storage and nitrous oxide emissions of cropping systems in eastern Washington: A simulation study

Stöckle¹,

Higgins²,

Kemanian³

et al. 2012

Journal of Soil and Water Conservation

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“…In the single-pool saturation model, an explicit microbial pool is not included, rather an effective C transfer efficiency between C r and C s lumps approximately three cycles of microbial predation into one step. This approach has been used to predict C storage accurately over decadal timescales (Kemanian and Stöckle, 2010), and a single-pool model offers the advantages of parsimony (Stewart et al, 2007) and simplicity of calibration requirements (Kemanian and Stöckle, . However, when coupled to a model of N mineralization, the single-pool saturation model yielded a r cr that ranged from 55 to over 555 as the C saturation ratio rose above 0.9 (Fig.…”

Section: Inclusion Of a Microbial Pool In C Saturation Models Affectsmentioning

confidence: 99%

Implications of carbon saturation model structures for simulated nitrogen mineralization dynamics

2014

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Abstract. Carbon (C) saturation theory suggests that soils have a limited capacity to stabilize organic C and that this capacity may be regulated by intrinsic soil properties such as clay concentration and mineralogy. While C saturation theory has advanced our ability to predict soil C stabilization, few biogeochemical ecosystem models have incorporated C saturation mechanisms. In biogeochemical models, C and nitrogen (N) cycling are tightly coupled, with C decomposition and respiration driving N mineralization. Thus, changing model structures from non-saturation to C saturation dynamics can change simulated N dynamics. In this study, we used C saturation models from the literature and of our own design to compare how different methods of modeling C saturation affected simulated N mineralization dynamics. Specifically, we tested (i) how modeling C saturation by regulating either the transfer efficiency (ε, g C retained g −1 C respired) or transfer rate (k) of C to stabilized pools affected N mineralization dynamics, (ii) how inclusion of an explicit microbial pool through which C and N must pass affected N mineralization dynamics, and (iii) whether using ε to implement C saturation in a model results in soil texture controls on N mineralization that are similar to those currently included in widely used non-saturating C and N models. Models were parameterized so that they rendered the same C balance. We found that when C saturation is modeled using ε, the critical C : N ratio for N mineralization from decomposing plant residues (r cr ) increases as C saturation of a soil increases. When C saturation is modeled using k, however, r cr is not affected by the C saturation of a soil. Inclusion of an explicit microbial pool in the model structure was necessary to capture short-term N immobilization-mineralization turnover dynamics during decomposition of low N residues. Finally, modeling C saturation by regulating ε led to similar soil texture controls on N mineralization as a widely used non-saturating model, suggesting that C saturation may be a fundamental mechanism that can explain N mineralization patterns across soil texture gradients. These findings indicate that a coupled C and N model that includes saturation can (1) represent short-term N mineralization by including a microbial pool and (2) express the effects of texture on N turnover as an emergent property.

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“…In order to simulate heterotrophic respiration (R h ), the CropSyst model apportions residue carbon into three fractions (fastand slow-cycling, and lignified fractions) with distinctive decomposition rates; and SOC into either single (Kemanian and Stöckle, 2010) or multiple (Stöckle et al, 2012) pools. Residue pools are initialized with the estimated contents of surface, root and residues from previous crops, while the SOC pool (singlepool model) is initialized based on the observed soil organic matter ( Table 3).…”

Section: Soil and Residue Respirationmentioning

confidence: 99%

Carbon and Water Budgets in Multiple Wheat-Based Cropping Systems in the Inland Pacific Northwest US: Comparison of CropSyst Simulations with Eddy Covariance Measurements

et al. 2017

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Accurate carbon and water flux simulations for croplands are greatly dependent on high quality representation of management practices and meteorological conditions, which are key drivers of the surface-atmosphere exchange processes. Fourteen site-years of carbon and water fluxes were simulated using the CropSyst model over four agricultural sites in the inland Pacific Northwest (iPNW) US from October 1, 2011 to September 30, 2015. Model performance for field-scale net ecosystem exchange of CO 2 (NEE) and evapotranspiration (ET) was evaluated by comparing simulations with long-term eddy covariance measurements. The model captured the temporal variations of NEE and ET reasonably well with an overall r of 0.78 and 0.80, and a low RMSE of 1.82 g C m −2 d −1 and 0.84 mm d −1 for NEE and ET, respectively. The model slightly underestimated NEE and ET by 0.51 g C m −2 d −1 and 0.09 mm d −1 , respectively. ET simulations showed better agreement with eddy covariance measurements than NEE. The model performed much better for the sites with detailed initial conditions (e.g., SOC content) and management practice information (e.g., tillage type). The CropSyst results showed that the winter wheat fields could be annual net carbon sinks or close to neutral with the net ecosystem carbon balance (NECB) ranging from 92 to −17 g C m −2 , while the spring crop fields were net carbon sources or neutral with an annual NECB of −327 to −3 g C m −2 . Simulations for the paired tillage sites showed that the no-till site resulted in lower CO 2 emissions for the crop rotations of winter wheat-spring garbanzo, but had higher carbon loss into the atmosphere for spring canola compared to the conventional tillage site. Water budgets did not differ significantly between the two tillage systems. Winter wheat in the high-rainfall area had higher crop yields and water use efficiency but emitted larger amounts of CO 2 into the atmosphere than in the low-rainfall area. Based Chi et al.Agricultural Carbon and Water Budgets on model evaluations in this study, CropSyst appears promising as a tool to simulate field-scale carbon and water budgets and assess the effects of different management practices and local meteorological conditions for the wheat-based cropping systems in this region.

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C-Farm: A simple model to evaluate the carbon balance of soil profiles

Cited by 59 publications

References 32 publications

Carbon storage and nitrous oxide emissions of cropping systems in eastern Washington: A simulation study

Carbon storage and nitrous oxide emissions of cropping systems in eastern Washington: A simulation study

Implications of carbon saturation model structures for simulated nitrogen mineralization dynamics

Carbon and Water Budgets in Multiple Wheat-Based Cropping Systems in the Inland Pacific Northwest US: Comparison of CropSyst Simulations with Eddy Covariance Measurements

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