Characterising effects of management practices, snow cover, and soil texture on soil temperature: Model development in DNDC. (April 2018)

• Record Type: Journal Article
• Authors: Dutta, Baishali; Grant, Brian B.; Congreves, Katelyn A.; Smith, Ward N.; Wagner-Riddle, Claudia; VanderZaag, Andrew C.; Tenuta, Mario; Desjardins, Raymond L.
• Is Part Of: Biosystems engineering. Volume 168(2018)
• Page Start: 54
• Page End: 72
• Publication Date: 2018-04
• Subjects: DNDC -- Soil temperature -- Model development -- Snow insulation -- Plant canopy; Bioengineering -- Periodicals; Agricultural engineering -- Periodicals; Biological systems -- Periodicals; Génie rural -- Périodiques; Systèmes biologiques -- Périodiques; 631
• DOI: 10.1016/j.biosystemseng.2017.02.001
• Languages: English
• ISSNs: 1537-5110

Abstract

Abstract : Agro-ecosystem models, such as the DNDC (DeNitrification and DeComposition) model are useful tools when assessing the sustainability of agricultural management. Accuracy in soil temperature estimations is important as it regulates many important soil biogeochemical processes that lead to greenhouse gas emissions (GHG). The objective of this study was to account for the effects of snow cover in terms of the measured snow depth (mm of water), soil texture and crop management in temperate latitudes in order to improve the surface soil temperature mechanism in DNDC and thereby improve GHG predictions. The estimation of soil temperature driven by the thermal conductivity and heat capacity of the soil was improved by considering the soil texture under frozen and unfrozen conditions along with the effects of crop canopy and snow depth. Calibration of the developed model mechanisms was conducted using data from Alfred, ON under two contrasting soil textures (sandy loam vs. clay). Independent validation assessments were conducted using soil temperatures at different depths for contrasting managements for two field sites located in Canada (Guelph, ON and Glenlea, MB). The validation results indicated high model accuracy (R 2 > 0.90, EF ≥ 0.90, RMSE < 3.00 °C) in capturing the effects of management on soil temperature. These developments in soil heat transfer mechanism improved the performance of the model in estimating N2 O emissions during spring thaw and provide a foundation for future studies aimed at improving simulations in DNDC for better representations of other biogeochemical processes. Highlights: Improved heat transfer mechanism for surface soil temperature in DNDC. Inclusion of snow cover, soil texture and crop management in temperate cold climates. Improved model gave very comparable overall result to observed values with low bias. Estimates of soil water content and snow pack were also well correlated. Improved model tested against measured non-growing season N2 O emissions.