Activity data on crop management define uncertainty of CH$_4$ and N$_2$O emission estimates from rice: A case study of Vietnam

Background: Globally, rice systems are a major source of atmospheric CH$_4$ and for major rice-producing countries, such as Vietnam, CH$_4$ as well as N$_2$O 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 CH$_4$ and N$_2$O from rice systems in Vietnam (Tier 3 IPCC approach). Our objectives were to identify hotspot regions of emissions and to assess the contribution of N$_2$O to the total non-CO$_2$ (CH$_4$+N$_2$O) 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 CH$_4$ and N$_2$O emissions from rice systems at a spatial resolution of 0.083° × 0.083°. ... mehrUncertainty in management practices related to fertilization, use of harvest residues or irrigation water, and its effects on simulated CH$_4$ and N$_2$O fluxes was accounted for by Latin Hypercube Sampling of probability distribution functions.
Results: Our study shows that CH$_4$ and N$_2$O fluxes from rice systems in Vietnam are highly seasonal, with national CH$_4$ and N$_2$O emissions totaling to about 2600 Gg CH$_4$ y$^{–1}$ and 42 Gg N$_2$O y$^{–1}$, 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 CO$_2$-eq Mg$^{–1}$ y$^{–1}$, with CH$_4$ emissions during the rice season(s) dominating (>82%) the total annual non-CO$_2$ 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 CH$_4$ and N$_2$O 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 CH$_4$, but as well for N$_2$O emissions. However, our study also shows that specifically better information on land management is required to narrowing uncertainties.