Skip to main content
ARS Home » Midwest Area » Ames, Iowa » National Laboratory for Agriculture and The Environment » Soil, Water & Air Resources Research » Research » Publications at this Location » Publication #305867

Research Project: MANAGEMENT OF AGRICULTURAL AND NATURAL RESOURCE SYSTEMS TO REDUCE ATMOSPHERIC EMISSIONS AND INCREASE RESILIENCE TO CLIMATE CHANGE

Location: Soil, Water & Air Resources Research

Title: Comparison of models for determining soil-surface carbon dioxide effluxes in different agricultural systems

Author
item Daigh, Aaron - North Dakota State University
item Sauer, Thomas - Tom
item Xiao, Xinhua - North Carolina State University
item Horton, Robert - Iowa State University

Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/27/2014
Publication Date: 4/6/2015
Citation: Daigh, A.L., Sauer, T.J., Xiao, X., Horton, R. 2015. Comparison of soil temperature- and water content-based models for determining soil-surface CO2 fluxes. Soil Science Society of America Journal. 107(3):1077-1086.

Interpretive Summary: Carbon dioxide (CO2) is a greenhouse gas. Soil management practices and cropping systems influence the amount of CO2 produced and released to the atmosphere. In this study, the amount of CO2 released from corn with and without a cover crop, soybean, and prairie systems with and without nitrogen fertilizer were measured every few days during the year. Different mathematical models were used to estimate the total amount of CO2 released by predicting the amount of CO2 released on the days between measurements. Soil temperature and water content data were used to predict soil CO2 release. Models developed from weekly average temperature and water content had smaller errors than when hourly data were used. Models that only used soil temperature rather than both temperature and water content were also more accurate. However, even the best model did not produce an estimate of CO2 release that was statistically different than a simple summing of the measured data. Some errors were associated with time so methods that could remove these errors make the models more effective. This research is of interest to policymakers, researchers, and land managers interested in improving estimates of annual CO2 release to the atmosphere from agricultural practices.

Technical Abstract: Soil-surface CO2 efflux (SCE) models are appealing due to expense and labor of fine temporal- and spatial-resolution field measurements. However, several simple SCE models are reported in the literature. Our objective was to compare and validate selected soil temperature (Ts)- and water content ('v)-based equations for modeling SCE and growing-season SCE among a variety of cropping systems and land management practices. Soil-surface CO2 effluxes were measured and modeled for grain-harvested corn-soybean rotations, grain- and stover-harvested continuous corn systems with and without a cover crop, and mixed reconstructed prairies with and without N fertilization on soils with a history of subsurface drainage. Soil-surface CO2 effluxes, Ts and 'v were monitored from 2008 to 2011. Models calibrated with weekly measured SCE, Ts and 'v produced lower RMSEs compared to models calibrated with hourly measured data. Model selection significantly affected SCE estimations with models that only use Ts parameters having lower RMSE than models that use both Ts and 'v. However, the model that produced the lowest RMSE during validation, estimated growing-season SCE that did not significantly differ from numerical integration of weekly measured SCE. All models had similar residual errors with autocorrelated temporal trends at both the monthly, weekly, and hourly time scales. The use of autoregressive moving average functions precisely described these temporal errors. To accurately model SCE and to scale across time, improvements of simple Ts- and 'v-based SCE models are needed if accurate and precise determination of carbon balances and useful land-management decision-making tools are to be obtained.