Evaluation of Parametric Limitations in Simulating Greenhouse Gas Fluxes from Irish Arable Soils Using Three Process-Based Models

Abstract

Globally a large number of process-based models have been assessed for quantification of agricultural greenhouse gas (GHG) emissions. Modelling approaches minimize the presence of spatial variability of biogeochemical processes, leading to improved estimates of GHGs as well as identifying mitigation and policy options. The comparative performance of the three dynamic models (e.g., DNDC v9.4, DailyDayCent and ECOSSE v5+) with minimum numbers of common input parameters was evaluated against measured variables. Simulations were performed on conventionally-tilled spring barley crops receiving N fertilizer at 135-159 kg•N•ha −1 •yr −1 and crop residues at 3 t•ha −1 •yr −1. For surface soil nitrate (0-10 cm), the ECOSSE and DNDC simulated values showed significant correlations with measured values (R 2 = 0.31-0.55, p < 0.05). Only the ECOSSE-simulated N2O fluxes showed a significant relationship (R 2 = 0.33, p < 0.05) with values measured from fertilized fields, but not with unfertilized ones. The DNDC and DailyDayCent models significantly underestimated seasonal/annual N2O fluxes compared to ECOSSE, with emission factors (EFs), based on an 8-year average, were 0.09%, 0.31% and 0.52%, respectively. Predictions of ecosystem respiration by both DailyDayCent and DNDC showed reasonable agreement with Eddy Covariance data (R 2 = 0.34-0.41, p < 0.05). Compared to the measured value (3624 kg•C•ha −1 •yr −1), the ECOSSE underestimated annual heterotrophic respiration by 7% but this was smaller than the DNDC (50%) and DailyDayCent (24%) estimates. All models simulated CH4 uptake well although the ECOSSE * Corresponding author. M. I. Khalil et al. 504 prediction was closer (−29 g•C•ha −1 •yr −1) to the measured one (2.9). The site-specific results imply that the ECOSSE model performed better under Irish conditions. However, further refinement and validation of all of the models with a more extensive dataset that includes other land-use and soil types will be required to determine their suitability in providing national estimates.

Calibration and validation of the DNDC model to estimate nitrous oxide emissions and crop productivity for a summer maize-winter wheat double cropping system in Hebei, China

“…Uncertainties in the observed values were also possible due to the limited number of field measurements (Parkin, 2008) as N2O is released in pulses from soils to the atmosphere (Hastings et al, 2010) and peaks may appear for a maximum of few weeks only (Bell et al, 2012). Khalil et al (2016) reported that it is important to use a robust measurement protocol to get accurate validation of the DNDC model in response to different management practices.…”

Multimodel Evaluation of Nitrous Oxide Emissions From an Intensively Managed Grassland

“…Previous studies have evaluated the models DayCent, PaSim, and APSIM with N 2 O flux data from lab experiments and on grassland sites under different climatic and soil conditions (Abdalla et al, ; Ehrhardt et al, ; Giltrap et al, ; Khalil et al, ; Y. Li et al, ; W. J. Parton et al, ; Stehfest & Müller, ; Thorburn et al, ; Xing et al, ). While some studies focused on the performance of the average N 2 O flux estimates across sites (Ehrhardt et al, ), most evaluated the dynamics of N 2 O fluxes, usually using manual chamber measurements (Abdalla et al, ; Giltrap et al, ; Khalil et al, ; Stehfest & Müller, ; Zimmermann et al, ). For instance, Fitton et al () showed relative biases for DayCent for three UK sites ranging from −84% to +10%.…”

Evaluation of denitrification from three biogeochemical models using laboratory measurements of N&lt;sub&gt;2&lt;/sub&gt;, N&lt;sub&gt;2&lt;/sub&gt;O and CO&lt;sub&gt;2&lt;/sub&gt;

“…It has been extensively tested globally and has shown reasonable agreements between measured and modeled N2O emissions for many different ecosystems (e.g. Li, 2007;Kurbatova et al, 2009;Giltrap et al, 2010;Khalil et al, 2016;2018;…”