Abstract
Methane (CH4) is an important greenhouse gas (GHG) that contributes to climate
change and one of its major sources is rice cultivation. The main aim of this paper was to compare two well-established biogeochemical models, namely Daily Century (DAYCENT) and DeNitrification-DeComposition (DNDC) for estimating CH4 emissions and grain yields for a double-rice cropping system with tillage practice and/or stubble incorporation in the winter fallow season in Southern China. Both models were calibrated and validated using field measured data from November 2008 to November 2014. The calibrated models performed effectively in estimating the daily CH4 emission pattern (correlation coefficient, r = 58−63, p < 0.001), but model efficiency (EF) values were higher in stubble incorporation treatments, with and without winter tillage (treatments S and WS) (EF = 0.22−0.28) than that in winter tillage without stubble incorporation treatment (W) (EF = −0.06−0.08). We recommend that algorithms for the impacts of tillage practice on CH4 emission should be improved for both models. DAYCENT and DNDC also estimated rice yields for all treatments without a significant bias. Our results showed that tillage practice in the winter fallow season (treatments WS and W) significantly decreased annual CH4 emissions, by 13−37% (p < 0.05) for measured values, 15−20% (p < 0.05) for DAYCENT-simulated values, and 12−32% (p < 0.05) for DNDC-simulated values,
respectively, compared to no-till practice (treatments S), but had no significant impact on grain yields.
change and one of its major sources is rice cultivation. The main aim of this paper was to compare two well-established biogeochemical models, namely Daily Century (DAYCENT) and DeNitrification-DeComposition (DNDC) for estimating CH4 emissions and grain yields for a double-rice cropping system with tillage practice and/or stubble incorporation in the winter fallow season in Southern China. Both models were calibrated and validated using field measured data from November 2008 to November 2014. The calibrated models performed effectively in estimating the daily CH4 emission pattern (correlation coefficient, r = 58−63, p < 0.001), but model efficiency (EF) values were higher in stubble incorporation treatments, with and without winter tillage (treatments S and WS) (EF = 0.22−0.28) than that in winter tillage without stubble incorporation treatment (W) (EF = −0.06−0.08). We recommend that algorithms for the impacts of tillage practice on CH4 emission should be improved for both models. DAYCENT and DNDC also estimated rice yields for all treatments without a significant bias. Our results showed that tillage practice in the winter fallow season (treatments WS and W) significantly decreased annual CH4 emissions, by 13−37% (p < 0.05) for measured values, 15−20% (p < 0.05) for DAYCENT-simulated values, and 12−32% (p < 0.05) for DNDC-simulated values,
respectively, compared to no-till practice (treatments S), but had no significant impact on grain yields.
| Original language | English |
|---|---|
| Article number | 116364 |
| Number of pages | 12 |
| Journal | Geoderma |
| Volume | 431 |
| Early online date | 10 Feb 2023 |
| DOIs | |
| Publication status | Published - Mar 2023 |
Bibliographical note
AcknowledgementsThis work contributed to the following projects: EU Horizon 2020 programme
(SuperG) and The Scientific and Technological Innovation Special Fund Project of
Carbon Peak and Carbon Neutrality in Jiangsu Province (No. BE2022311). The first author (Yang Guo) gratefully acknowledges financial support from China Scholarship Council (CSC).
Data Availability Statement
Data will be made available on request.Keywords
- Methane
- Management practices
- DAYCENT model
- DNDC model
- Double-rice cropping system
- China
Access to Document
- Guo_etal_GD_Modeling _Methane_Emissions_VOR
/© 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).