Estimating greenhouse gases emissions from horticultural peat soils using a DNDC modelling approach
Research output: Contribution to journal › Article › peer-review
Standard Standard
In: Journal of Environmental Management, Vol. 233, 01.03.2019, p. 681-694.
Research output: Contribution to journal › Article › peer-review
HarvardHarvard
APA
CBE
MLA
VancouverVancouver
Author
RIS
TY - JOUR
T1 - Estimating greenhouse gases emissions from horticultural peat soils using a DNDC modelling approach
AU - Taft, Helen E.
AU - Cross, Paul A.
AU - Hastings, Astley
AU - Yeluripati, Jagadeesh
AU - Jones, Davey L.
PY - 2019/3/1
Y1 - 2019/3/1
N2 - Peat soils represent an important global carbon (C) sink, but can also provide a highly fertile medium for growing horticultural crops. Sustainable crop production on peat soils involves a trade-off between ensuring food security and mitigating typically high greenhouse gas (GHG) emissions and rates of soil C loss. An alternative approach to resource intensive field-based monitoring of GHG fluxes for all potential management scenarios is to use a process-based model driven by existing field data to estimate emissions. The aim of this study was to evaluate the suitability of the Denitrification-Decomposition (DNDC) model for estimating emissions of CO2, N2O and CH4 from horticultural peat soils. The model was parameterised using climatic, soil, and crop management data from two intensively cultivated sites on soils of contrasting soil organic matter (SOM) contents (∼35% and ∼70% SOM content). Simulated emissions of CO2, N2O and CH4, and simulated soil physical and crop output values, were compared to actual GHG, soil and crop measurements. Model performance was assessed using baseline parameterisation (i.e. model defaults), then calibrated using pre-simulation and sensitivity analysis processes. Under baseline parameterisation conditions, DNDC proved poor at predicting GHG emissions and soil/crop variables. Calibration and validation improved DNDC performance in estimating the annual magnitude of emissions, but model refinement is still required for reproducing seasonal GHG patterns in particular. Key constraints on model functioning appear to be its ability to reliably model soil moisture and some aspects of C and nitrogen dynamics, as well as the quality of input data relating to water table dynamics. In conclusion, our results suggest that the DNDC (v. 9.5) model cannot accurately reproduce or be used to replace actual field measurements for estimation of GHG emission factors under different management scenarios for horticultural peat soils, but may be able to do so with further modification.
AB - Peat soils represent an important global carbon (C) sink, but can also provide a highly fertile medium for growing horticultural crops. Sustainable crop production on peat soils involves a trade-off between ensuring food security and mitigating typically high greenhouse gas (GHG) emissions and rates of soil C loss. An alternative approach to resource intensive field-based monitoring of GHG fluxes for all potential management scenarios is to use a process-based model driven by existing field data to estimate emissions. The aim of this study was to evaluate the suitability of the Denitrification-Decomposition (DNDC) model for estimating emissions of CO2, N2O and CH4 from horticultural peat soils. The model was parameterised using climatic, soil, and crop management data from two intensively cultivated sites on soils of contrasting soil organic matter (SOM) contents (∼35% and ∼70% SOM content). Simulated emissions of CO2, N2O and CH4, and simulated soil physical and crop output values, were compared to actual GHG, soil and crop measurements. Model performance was assessed using baseline parameterisation (i.e. model defaults), then calibrated using pre-simulation and sensitivity analysis processes. Under baseline parameterisation conditions, DNDC proved poor at predicting GHG emissions and soil/crop variables. Calibration and validation improved DNDC performance in estimating the annual magnitude of emissions, but model refinement is still required for reproducing seasonal GHG patterns in particular. Key constraints on model functioning appear to be its ability to reliably model soil moisture and some aspects of C and nitrogen dynamics, as well as the quality of input data relating to water table dynamics. In conclusion, our results suggest that the DNDC (v. 9.5) model cannot accurately reproduce or be used to replace actual field measurements for estimation of GHG emission factors under different management scenarios for horticultural peat soils, but may be able to do so with further modification.
KW - DNDC
KW - Drained peatlands
KW - Greenhouse gas
KW - Histosol
KW - Model validation
KW - Vegetable production
U2 - 10.1016/j.jenvman.2018.11.113
DO - 10.1016/j.jenvman.2018.11.113
M3 - Article
VL - 233
SP - 681
EP - 694
JO - Journal of Environmental Management
JF - Journal of Environmental Management
SN - 0301-4797
ER -