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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 5
Geosci. Model Dev., 11, 1909-1928, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 11, 1909-1928, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model description paper 28 May 2018

Model description paper | 28 May 2018

Modeling soil CO2 production and transport with dynamic source and diffusion terms: testing the steady-state assumption using DETECT v1.0

Edmund M. Ryan1,2, Kiona Ogle2,3,4,5, Heather Kropp6, Kimberly E. Samuels-Crow3, Yolima Carrillo7, and Elise Pendall7 Edmund M. Ryan et al.
  • 1Lancaster Environment Centre, Lancaster University, Lancaster, UK
  • 2School of Life Sciences, Arizona State University, Tempe, Arizona, USA
  • 3School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona, USA
  • 4Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, Arizona, USA
  • 5Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona, USA
  • 6Department of Geography, Colgate University, Hamilton, New York, USA
  • 7Hawkesbury Institute for the Environment, Western Sydney University, NSW, Australia

Abstract. The flux of CO2 from the soil to the atmosphere (soil respiration, Rsoil) is a major component of the global carbon (C) cycle. Methods to measure and model Rsoil, or partition it into different components, often rely on the assumption that soil CO2 concentrations and fluxes are in steady state, implying that Rsoil is equal to the rate at which CO2 is produced by soil microbial and root respiration. Recent research, however, questions the validity of this assumption. Thus, the aim of this work was two-fold: (1) to describe a non-steady state (NSS) soil CO2 transport and production model, DETECT, and (2) to use this model to evaluate the environmental conditions under which Rsoil and CO2 production are likely in NSS. The backbone of DETECT is a non-homogeneous, partial differential equation (PDE) that describes production and transport of soil CO2, which we solve numerically at fine spatial and temporal resolution (e.g., 0.01m increments down to 1m, every 6h). Production of soil CO2 is simulated for every depth and time increment as the sum of root respiration and microbial decomposition of soil organic matter. Both of these factors can be driven by current and antecedent soil water content and temperature, which can also vary by time and depth. We also analytically solved the ordinary differential equation (ODE) corresponding to the steady-state (SS) solution to the PDE model. We applied the DETECT NSS and SS models to the six-month growing season period representative of a native grassland in Wyoming. Simulation experiments were conducted with both model versions to evaluate factors that could affect departure from SS, such as (1) varying soil texture; (2) shifting the timing or frequency of precipitation; and (3) with and without the environmental antecedent drivers. For a coarse-textured soil, Rsoil from the SS model closely matched that of the NSS model. However, in a fine-textured (clay) soil, growing season Rsoil was  ∼ 3% higher under the assumption of NSS (versus SS). These differences were exaggerated in clay soil at daily time scales whereby Rsoil under the SS assumption deviated from NSS by up to 35% on average in the 10 days following a major precipitation event. Incorporation of antecedent drivers increased the magnitude of Rsoil by 15 to 37% for coarse- and fine-textured soils, respectively. However, the responses of Rsoil to the timing of precipitation and antecedent drivers did not differ between SS and NSS assumptions. In summary, the assumption of SS conditions can be violated depending on soil type and soil moisture status, as affected by precipitation inputs. The DETECT model provides a framework for accommodating NSS conditions to better predict Rsoil and associated soil carbon cycling processes.

Publications Copernicus
Short summary
Our work evaluated the appropriateness of the common steady-state (SS) assumption, for example when partitioning soil respiration of CO2 into recently photosynthesized carbon (C) and older C. Using a new model of soil CO2 production and transport we found that the SS assumption is valid most of the time, especially in sand/silt soils. Non-SS conditions occurred mainly for the few days following large rain events in all soil types, but the non-SS period was prolonged and magnified in clay soils.
Our work evaluated the appropriateness of the common steady-state (SS) assumption, for example...