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Modelling methane emissions and grain yields for a double-rice system in Southern China with DAYCENT and DNDC models
Methane (CH(4)) is an important greenhouse gas 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 estima...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Scientific Pub. Co
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10035045/ https://www.ncbi.nlm.nih.gov/pubmed/36968674 http://dx.doi.org/10.1016/j.geoderma.2023.116364 |
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author | Guo, Yang Zhang, Guangbin Abdalla, Mohamed Kuhnert, Matthias Bao, Haijun Xu, Hua Ma, Jing Begum, Khadiza Smith, Pete |
author_facet | Guo, Yang Zhang, Guangbin Abdalla, Mohamed Kuhnert, Matthias Bao, Haijun Xu, Hua Ma, Jing Begum, Khadiza Smith, Pete |
author_sort | Guo, Yang |
collection | PubMed |
description | Methane (CH(4)) is an important greenhouse gas 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 CH(4) 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 CH(4) emission pattern (correlation coefficient, r = 0.58–0.63, 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 CH(4) 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 CH(4) 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. |
format | Online Article Text |
id | pubmed-10035045 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier Scientific Pub. Co |
record_format | MEDLINE/PubMed |
spelling | pubmed-100350452023-03-24 Modelling methane emissions and grain yields for a double-rice system in Southern China with DAYCENT and DNDC models Guo, Yang Zhang, Guangbin Abdalla, Mohamed Kuhnert, Matthias Bao, Haijun Xu, Hua Ma, Jing Begum, Khadiza Smith, Pete Geoderma Article Methane (CH(4)) is an important greenhouse gas 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 CH(4) 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 CH(4) emission pattern (correlation coefficient, r = 0.58–0.63, 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 CH(4) 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 CH(4) 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. Elsevier Scientific Pub. Co 2023-03 /pmc/articles/PMC10035045/ /pubmed/36968674 http://dx.doi.org/10.1016/j.geoderma.2023.116364 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Guo, Yang Zhang, Guangbin Abdalla, Mohamed Kuhnert, Matthias Bao, Haijun Xu, Hua Ma, Jing Begum, Khadiza Smith, Pete Modelling methane emissions and grain yields for a double-rice system in Southern China with DAYCENT and DNDC models |
title | Modelling methane emissions and grain yields for a double-rice system in Southern China with DAYCENT and DNDC models |
title_full | Modelling methane emissions and grain yields for a double-rice system in Southern China with DAYCENT and DNDC models |
title_fullStr | Modelling methane emissions and grain yields for a double-rice system in Southern China with DAYCENT and DNDC models |
title_full_unstemmed | Modelling methane emissions and grain yields for a double-rice system in Southern China with DAYCENT and DNDC models |
title_short | Modelling methane emissions and grain yields for a double-rice system in Southern China with DAYCENT and DNDC models |
title_sort | modelling methane emissions and grain yields for a double-rice system in southern china with daycent and dndc models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10035045/ https://www.ncbi.nlm.nih.gov/pubmed/36968674 http://dx.doi.org/10.1016/j.geoderma.2023.116364 |
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