Activity data on crop management define uncertainty of CH4 and N2O emission estimates from rice: A case study of Vietnam

Background Globally, rice systems are a major source of atmospheric CH4 and for major rice‐producing countries, such as Vietnam, CH4 as well as N2O emissions from agricultural land used for rice production may represent about one‐fourth of total national anthropogenic greenhouse gas (GHG) emissions....

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Veröffentlicht in:Journal of plant nutrition and soil science 2022-12, Vol.185 (6), p.793-806
Hauptverfasser: Butterbach‐Bahl, Klaus, Kraus, David, Kiese, Ralf, Mai, Van Trinh, Nguyen, Tanh, Sander, Björn Ole, Wassmann, Reiner, Werner, Christian
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container_issue 6
container_start_page 793
container_title Journal of plant nutrition and soil science
container_volume 185
creator Butterbach‐Bahl, Klaus
Kraus, David
Kiese, Ralf
Mai, Van Trinh
Nguyen, Tanh
Sander, Björn Ole
Wassmann, Reiner
Werner, Christian
description Background Globally, rice systems are a major source of atmospheric CH4 and for major rice‐producing countries, such as Vietnam, CH4 as well as N2O emissions from agricultural land used for rice production may represent about one‐fourth of total national anthropogenic greenhouse gas (GHG) emissions. However, national‐scale estimates of GHG emissions from rice systems are uncertain with regard to its magnitude, spatial distribution, and seasonality. Aims Here, we used the biogeochemical model LandscapeDNDC to calculate emissions of CH4 and N2O from rice systems in Vietnam (Tier 3 IPCC approach). Our objectives were to identify hotspot regions of emissions and to assess the contribution of N2O to the total non‐CO2 (CH4+N2O) GHG balance of rice systems as well as the seasonal and interannual variability of fluxes in dependence of uncertain input data on field management . Methods The biogeochemical model LandscapeDNDC model was linked to publicly available information on climate, soils, and land management (fertilization, irrigation, crop rotation) for calculating a national inventory in daily time steps of CH4 and N2O emissions from rice systems at a spatial resolution of 0.083° × 0.083°. Uncertainty in management practices related to fertilization, use of harvest residues or irrigation water, and its effects on simulated CH4 and N2O fluxes was accounted for by Latin Hypercube Sampling of probability distribution functions. Results Our study shows that CH4 and N2O fluxes from rice systems in Vietnam are highly seasonal, with national CH4 and N2O emissions totaling to about 2600 Gg CH4 year–1 and 42 Gg N2O year–1, respectively. Highest emissions were simulated for double and triple rice cropping systems in the Mekong Delta region. Yield‐scaled emissions varied largely in a range of 300–3000 kg CO2‐eq Mg–1 year–1, with CH4 emissions during the rice season(s) dominating (>82%) the total annual non‐CO2 GHG balance of rice systems. In our study, uncertainty in field management information (nitrogen fertilization, ratio synthetic to organic fertilization, residue management, availability of irrigation water) were major drivers of uncertainty of the national CH4 and N2O emission inventory. Conclusions Our study shows that Tier 3 approaches, that is, process‐oriented model approaches combined with GIS databases, for estimating national‐scale GHG emissions from rice systems are ready to be applied at national scale. Generally, this approach is powerful as it allows t
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However, national‐scale estimates of GHG emissions from rice systems are uncertain with regard to its magnitude, spatial distribution, and seasonality. Aims Here, we used the biogeochemical model LandscapeDNDC to calculate emissions of CH4 and N2O from rice systems in Vietnam (Tier 3 IPCC approach). Our objectives were to identify hotspot regions of emissions and to assess the contribution of N2O to the total non‐CO2 (CH4+N2O) GHG balance of rice systems as well as the seasonal and interannual variability of fluxes in dependence of uncertain input data on field management . Methods The biogeochemical model LandscapeDNDC model was linked to publicly available information on climate, soils, and land management (fertilization, irrigation, crop rotation) for calculating a national inventory in daily time steps of CH4 and N2O emissions from rice systems at a spatial resolution of 0.083° × 0.083°. Uncertainty in management practices related to fertilization, use of harvest residues or irrigation water, and its effects on simulated CH4 and N2O fluxes was accounted for by Latin Hypercube Sampling of probability distribution functions. Results Our study shows that CH4 and N2O fluxes from rice systems in Vietnam are highly seasonal, with national CH4 and N2O emissions totaling to about 2600 Gg CH4 year–1 and 42 Gg N2O year–1, respectively. Highest emissions were simulated for double and triple rice cropping systems in the Mekong Delta region. Yield‐scaled emissions varied largely in a range of 300–3000 kg CO2‐eq Mg–1 year–1, with CH4 emissions during the rice season(s) dominating (&gt;82%) the total annual non‐CO2 GHG balance of rice systems. In our study, uncertainty in field management information (nitrogen fertilization, ratio synthetic to organic fertilization, residue management, availability of irrigation water) were major drivers of uncertainty of the national CH4 and N2O emission inventory. Conclusions Our study shows that Tier 3 approaches, that is, process‐oriented model approaches combined with GIS databases, for estimating national‐scale GHG emissions from rice systems are ready to be applied at national scale. Generally, this approach is powerful as it allows to identify regions with elevated emissions, thereby accounting not only for CH4, but as well for N2O emissions. However, our study also shows that specifically better information on land management is required to narrowing uncertainties.</description><identifier>ISSN: 1436-8730</identifier><identifier>EISSN: 1522-2624</identifier><identifier>DOI: 10.1002/jpln.202200382</identifier><language>eng</language><publisher>Weinheim: Wiley Subscription Services, Inc</publisher><subject>Agricultural land ; Agricultural practices ; Anthropogenic factors ; Availability ; biogeochemical modeling ; Biogeochemistry ; Carbon dioxide ; Cereal crops ; Crop management ; Crop production ; Crop rotation ; Cropping systems ; Distribution functions ; Emission analysis ; Emission inventories ; Emissions ; Estimates ; Farm buildings ; Fertilization ; field management ; Fluxes ; Greenhouse gases ; Hypercubes ; Information management ; Intergovernmental Panel on Climate Change ; Irrigation ; Irrigation water ; Land management ; Land use planning ; Latin hypercube sampling ; Methane ; Nitrous oxide ; Organic fertilizers ; Probability distribution ; Probability distribution functions ; Residues ; Rice ; Rice fields ; rice systems ; Seasonal distribution ; Seasonal variations ; soil CH4 and N2O emissions ; Spatial discrimination ; Spatial distribution ; Spatial resolution ; Uncertainty ; uncertainty assessment</subject><ispartof>Journal of plant nutrition and soil science, 2022-12, Vol.185 (6), p.793-806</ispartof><rights>2022 The Authors. Journal of Plant Nutrition and Soil Science published by Wiley‐VCH GmbH</rights><rights>2022. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-0847-4185 ; 0000-0001-7032-8683 ; 0000-0003-2485-8389 ; 0000-0002-7967-6147 ; 0000-0002-2814-4888 ; 0000-0001-9499-6598</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjpln.202200382$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjpln.202200382$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids></links><search><creatorcontrib>Butterbach‐Bahl, Klaus</creatorcontrib><creatorcontrib>Kraus, David</creatorcontrib><creatorcontrib>Kiese, Ralf</creatorcontrib><creatorcontrib>Mai, Van Trinh</creatorcontrib><creatorcontrib>Nguyen, Tanh</creatorcontrib><creatorcontrib>Sander, Björn Ole</creatorcontrib><creatorcontrib>Wassmann, Reiner</creatorcontrib><creatorcontrib>Werner, Christian</creatorcontrib><title>Activity data on crop management define uncertainty of CH4 and N2O emission estimates from rice: A case study of Vietnam</title><title>Journal of plant nutrition and soil science</title><description>Background Globally, rice systems are a major source of atmospheric CH4 and for major rice‐producing countries, such as Vietnam, CH4 as well as N2O emissions from agricultural land used for rice production may represent about one‐fourth of total national anthropogenic greenhouse gas (GHG) emissions. However, national‐scale estimates of GHG emissions from rice systems are uncertain with regard to its magnitude, spatial distribution, and seasonality. Aims Here, we used the biogeochemical model LandscapeDNDC to calculate emissions of CH4 and N2O from rice systems in Vietnam (Tier 3 IPCC approach). Our objectives were to identify hotspot regions of emissions and to assess the contribution of N2O to the total non‐CO2 (CH4+N2O) GHG balance of rice systems as well as the seasonal and interannual variability of fluxes in dependence of uncertain input data on field management . Methods The biogeochemical model LandscapeDNDC model was linked to publicly available information on climate, soils, and land management (fertilization, irrigation, crop rotation) for calculating a national inventory in daily time steps of CH4 and N2O emissions from rice systems at a spatial resolution of 0.083° × 0.083°. Uncertainty in management practices related to fertilization, use of harvest residues or irrigation water, and its effects on simulated CH4 and N2O fluxes was accounted for by Latin Hypercube Sampling of probability distribution functions. Results Our study shows that CH4 and N2O fluxes from rice systems in Vietnam are highly seasonal, with national CH4 and N2O emissions totaling to about 2600 Gg CH4 year–1 and 42 Gg N2O year–1, respectively. Highest emissions were simulated for double and triple rice cropping systems in the Mekong Delta region. Yield‐scaled emissions varied largely in a range of 300–3000 kg CO2‐eq Mg–1 year–1, with CH4 emissions during the rice season(s) dominating (&gt;82%) the total annual non‐CO2 GHG balance of rice systems. In our study, uncertainty in field management information (nitrogen fertilization, ratio synthetic to organic fertilization, residue management, availability of irrigation water) were major drivers of uncertainty of the national CH4 and N2O emission inventory. Conclusions Our study shows that Tier 3 approaches, that is, process‐oriented model approaches combined with GIS databases, for estimating national‐scale GHG emissions from rice systems are ready to be applied at national scale. Generally, this approach is powerful as it allows to identify regions with elevated emissions, thereby accounting not only for CH4, but as well for N2O emissions. 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However, national‐scale estimates of GHG emissions from rice systems are uncertain with regard to its magnitude, spatial distribution, and seasonality. Aims Here, we used the biogeochemical model LandscapeDNDC to calculate emissions of CH4 and N2O from rice systems in Vietnam (Tier 3 IPCC approach). Our objectives were to identify hotspot regions of emissions and to assess the contribution of N2O to the total non‐CO2 (CH4+N2O) GHG balance of rice systems as well as the seasonal and interannual variability of fluxes in dependence of uncertain input data on field management . Methods The biogeochemical model LandscapeDNDC model was linked to publicly available information on climate, soils, and land management (fertilization, irrigation, crop rotation) for calculating a national inventory in daily time steps of CH4 and N2O emissions from rice systems at a spatial resolution of 0.083° × 0.083°. Uncertainty in management practices related to fertilization, use of harvest residues or irrigation water, and its effects on simulated CH4 and N2O fluxes was accounted for by Latin Hypercube Sampling of probability distribution functions. Results Our study shows that CH4 and N2O fluxes from rice systems in Vietnam are highly seasonal, with national CH4 and N2O emissions totaling to about 2600 Gg CH4 year–1 and 42 Gg N2O year–1, respectively. Highest emissions were simulated for double and triple rice cropping systems in the Mekong Delta region. Yield‐scaled emissions varied largely in a range of 300–3000 kg CO2‐eq Mg–1 year–1, with CH4 emissions during the rice season(s) dominating (&gt;82%) the total annual non‐CO2 GHG balance of rice systems. In our study, uncertainty in field management information (nitrogen fertilization, ratio synthetic to organic fertilization, residue management, availability of irrigation water) were major drivers of uncertainty of the national CH4 and N2O emission inventory. Conclusions Our study shows that Tier 3 approaches, that is, process‐oriented model approaches combined with GIS databases, for estimating national‐scale GHG emissions from rice systems are ready to be applied at national scale. Generally, this approach is powerful as it allows to identify regions with elevated emissions, thereby accounting not only for CH4, but as well for N2O emissions. 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subjects Agricultural land
Agricultural practices
Anthropogenic factors
Availability
biogeochemical modeling
Biogeochemistry
Carbon dioxide
Cereal crops
Crop management
Crop production
Crop rotation
Cropping systems
Distribution functions
Emission analysis
Emission inventories
Emissions
Estimates
Farm buildings
Fertilization
field management
Fluxes
Greenhouse gases
Hypercubes
Information management
Intergovernmental Panel on Climate Change
Irrigation
Irrigation water
Land management
Land use planning
Latin hypercube sampling
Methane
Nitrous oxide
Organic fertilizers
Probability distribution
Probability distribution functions
Residues
Rice
Rice fields
rice systems
Seasonal distribution
Seasonal variations
soil CH4 and N2O emissions
Spatial discrimination
Spatial distribution
Spatial resolution
Uncertainty
uncertainty assessment
title Activity data on crop management define uncertainty of CH4 and N2O emission estimates from rice: A case study of Vietnam
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