• Energy Research

Traditional irrigated double-rice cropping systems have to cope with reduced water availability due to changes of climate and economic conditions. To quantify the shift in CH4 and N2O emissions when changing from traditional to diversified double cropping-systems, an experiment including flooded rice, non-flooded “aerobic” rice and maize was conducted during the dry season (February–June 2012) in the Philippines. Two automated static chamber–GC systems were used to continuously measure CH4 and N2O emissions in the three cropping systems of which each included three different nitrogen fertilization regimes. Turning away from flooded cropping systems leads to shifts in greenhouse gas emissions from CH4 under wet soil to N2O emissions under drier soil conditions. The global warming potential (GWP) of the non-flooded crops was lower compared to flooded rice, whereas high CH4 emissions under flooded conditions still override enhanced N2O emissions in the upland systems. The yield-scaled GWP favored maize over aerobic rice, due to lower yields of aerobic rice. However, the lower GHG emissions of upland systems are only beneficial if they are not overwhelmed by enhanced losses of soil organic carbon.

AbstractBackgroundGlobally, 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.AimsHere, 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 .MethodsThe 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.ResultsOur 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.ConclusionsOur 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.

AbstractAccurate quantification of landscape soil greenhouse gas (GHG) exchange from chamber measurements is challenging due to the high spatial‐temporal variability of fluxes, which results in large uncertainties in upscaled regional and global flux estimates. We quantified landscape‐scale (6 km2 in central Germany) soil/ecosystem respiration (SR/ER‐CO2), methane (CH4), and nitrous oxide (N2O) fluxes at stratified sites with contrasting landscape characteristics using the fast‐box chamber technique. We assessed the influence of land use (forest, arable, and grassland), seasonality (spring, summer, and autumn), soil types, and slope on the fluxes. We also evaluated the number of chamber measurement locations required to estimate landscape fluxes within globally significant uncertainty thresholds. The GHG fluxes were strongly influenced by seasonality and land use rather than soil type and slope. The number of chamber measurement locations required for robust landscape‐scale flux estimates depended on the magnitude of fluxes, which varied with season, land use, and GHG type. Significant N2O‐N flux uncertainties greater than the global mean flux (0.67 kg ha−1 yr−1) occurred if landscape measurements were done at <4 and <22 chamber locations (per km2) in forest and arable ecosystems, respectively, in summer. For CO2 and CH4 fluxes, uncertainties greater than the global median CO2‐C flux (7,500 kg ha−1 yr−1) and the global mean forest CH4‐C uptake rate (2.81 kg ha−1 yr−1) occurred at <2 forest and <6 arable chamber locations. This finding suggests that more chamber measurement locations are required to assess landscape‐scale N2O fluxes than CO2 and CH4, based on these GHG‐specific uncertainty thresholds.

AbstractGlobal rice agriculture will be increasingly challenged by water scarcity, while at the same time changes in demand (e.g. changes in diets or increasing demand for biofuels) will feed back on agricultural practices. These factors are changing traditional cropping patterns from double‐rice cropping to the introduction of upland crops in the dry season. For a comprehensive assessment of greenhouse gas (GHG) balances, we measured methane (CH4)/nitrous oxide (N2O) emissions and agronomic parameters over 2.5 years in double‐rice cropping (R‐R) and paddy rice rotations diversified with either maize (R‐M) or aerobic rice (R‐A) in upland cultivation. Introduction of upland crops in the dry season reduced irrigation water use and CH4 emissions by 66–81% and 95–99%, respectively. Moreover, for practices including upland crops, CH4 emissions in the subsequent wet season with paddy rice were reduced by 54–60%. Although annual N2O emissions increased two‐ to threefold in the diversified systems, the strong reduction in CH4 led to a significantly lower (P < 0.05) annual GWP (CH4 + N2O) as compared to the traditional double‐rice cropping system. Measurements of soil organic carbon (SOC) contents before and 3 years after the introduction of upland crop rotations indicated a SOC loss for the R‐M system, while for the other systems SOC stocks were unaffected. This trend for R‐M systems needs to be followed as it has significant consequences not only for the GWP balance but also with regard to soil fertility. Economic assessment showed a similar gross profit span for R‐M and R‐R, while gross profits for R‐A were reduced as a consequence of lower productivity. Nevertheless, regarding a future increase in water scarcity, it can be expected that mixed lowland–upland systems will expand in SE Asia as water requirements were cut by more than half in both rotation systems with upland crops.

AbstractWorldwide, rice production contributes about 10% of total greenhouse gas (GHG) emissions from the agricultural sector, mainly due to CH4 emissions from continuously flooded fields. Alternate Wetting and Drying (AWD) is a promising crop technology for mitigating CH4 emissions and reducing the irrigation water currently being applied in many of the world's top rice‐producing countries. However, decreased emissions of CH4 may be partially counterbalanced by increased N2O emissions. In this case study for the Philippines, the national mitigation potential of AWD is explored using the process‐based biogeochemical model LandscapeDNDC. Simulated mean annual CH4 emissions under conventional rice production for the time period 2000–2011 are estimated as 1,180 ± 163 Gg CH4 yr−1. During the cropping season, this is about +16% higher than a former estimate using emission factors. Scenario simulations of nationwide introduction of AWD in irrigated landscapes suggest a considerable decrease in CH4 emissions by −23%, while N2O emissions are only increased by +8%. Irrespective of field management, at national scale, the radiative forcing of irrigated rice production is always dominated by CH4 (>95%). The reduction potential of GHG emissions depends on, for example, number of crops per year, residue management, amount of applied irrigation water, and sand content. Seasonal weather conditions also play an important role since the mitigation potential of AWD is almost double as high in dry as compared to wet seasons. Furthermore, this study demonstrates the importance of temporal continuity, considering off‐season emissions and the long‐term development of GHG emissions across multiple years.

The rising atmospheric CO2 concentrations have effects on the worldwide ecosystems such as an increase in biomass production as well as changing soil processes and conditions. Since this affects the ecosystem’s net balance of greenhouse gas emissions, reliable projections about the CO2 impact are required. Deterministic models can capture the interrelated biological, hydrological, and biogeochemical processes under changing CO2 concentrations if long-term observations for model testing are provided. We used 13 years of data on above-ground biomass production, soil moisture, and emissions of CO2 and N2O from the Free Air Carbon dioxide Enrichment (FACE) grassland experiment in Giessen, Germany. Then, the LandscapeDNDC ecosystem model was calibrated with data measured under current CO2 concentrations and validated under elevated CO2. Depending on the hydrological conditions, different CO2 effects were observed and captured well for all ecosystem variables but N2O emissions. Confidence intervals of ensemble simulations covered up to 96% of measured biomass and CO2 emission values, while soil water content was well simulated in terms of annual cycle and location-specific CO2 effects. N2O emissions under elevated CO2 could not be reproduced, presumably due to a rarely considered mineralization process of organic nitrogen, which is not yet included in LandscapeDNDC.

AbstractWe applied the process-based model, LandscapeDNDC, to estimate feed availability in the Sahelian and Sudanian agro-ecological zones of West Africa as a basis for calculating the regional Livestock Carrying Capacity (LCC). Comparison of the energy supply (S) from feed resources, including natural pasture, browse, and crop residues, with energy demand (D) of the livestock population for the period 1981–2020 allowed us to assess regional surpluses (S > D) or deficits (S < D) in feed availability. We show that in the last 40 years a large-scale shift from surplus to deficit has occurred. While during 1981–1990 only 27% of the area exceeded the LCC, it was 72% for the period 2011–2020. This was caused by a reduction in the total feed supply of ~ 8% and an increase in feed demand of ~ 37% per-decade, driven by climate change and increased livestock population, respectively. Overall, the S/D decreased from ~ 2.6 (surplus) in 1981 to ~ 0.5 (deficit) in 2019, with a north–south gradient of increasing S/D. As climate change continues and feed availability may likely further shrink, pastoralists either need to source external feed or significantly reduce livestock numbers to avoid overgrazing, land degradation, and any further conflicts for resources.