Modellierung und Regionalisierung von Treibhausgas-Emissionen und Nitratauswaschung
Zusammenfassung der Projektergebnisse
The LandscapeDNDC model framework was successively expanded by the new soil biogeochemical model MeTrx and the vegetation models PlaMox and L-ORYZA that allow the accurate simulation of GHG emissions from rice based cropping systems under varying field management scenarios. The newly developed models were extensively tested against field site measurements (CH4: R2 = 0.85, N2O: R2 = 0.78) that have been compiled within the ICON project (mainly SP5) as well as further datasets from, e.g., the Philippines and Vietnam. In addition to model development, a model input preprocessing toolbox was developed that automates the creation of site to regional/global large-scale model input for the creation of GHG emissions inventories. The toolbox includes global soil maps and weather databases and facilitates the generation of field management. The toolbox followed a generic approach and in the meantime forms the basis for, e.g., the LandscapeDNDC web-based decision support tool for pasture growth. Two regional GHG inventories were created one for the Philippines and one for Vietnam. The Vietnam inventory focused on the uncertainties that are related with national simulation studies. Field management, especially the amount of harvest residues and application or organic manure as well as the applied irrigation water were discovered as the major drivers of uncertainties predominating over climatic and edaphic properties. The Philippines inventory investigated the effect of land management change, i.e., changing conventional field management with continuously flooded fields (CF) to Alternating Wetting and Drying (AWD). The nationwide implementation of AWD reduced CH4 emissions by 30%, while N2O emissions were only slightly increased. Potential reduction of GHG emissions was particularly restricted by climatic factors, i.e., abundant rainfall during wet seasons. In addition to the reduction potential, the Philippines inventory demonstrated the possibly large contribution of off-season GHG emissions to total annual budgets. Emissions of CH4 during land preparation and fallow period contributed 20% to annual CH4 emissions. This result is of particular importance since off-season GHG emissions are so far not part of IPCC-based inventories.
Projektbezogene Publikationen (Auswahl)
- 2014, A new LandscapeDNDC biogeochemical module to predict CH4 and N2O emissions from lowland rice and upland cropping systems. Plant Soil 386, 125-149
Kraus D, Weller S, Klatt S, Haas E, Wassmann R, Kiese R, Butterbach-Bahl K
(Siehe online unter https://doi.org/10.1007/s11104-014-2255-x) - 2015, Diurnal patterns of methane emissions from paddy rice fields at the Philippines. J. Plant Nutr. Soil Sci., 178, 755-767
Weller S, Kraus D, Butterbach‐Bahl K, Wassmann R, Tirol‐Padre A, Kiese R
(Siehe online unter https://doi.org/10.1002/jpln.201500092) - 2015, Methane and nitrous oxide emissions from rice and maize production in diversified rice cropping systems. Nutr. Cycl. Agroecosys. 101, 37-53
Weller S, Kraus D, Ayag KRP, Wassmann R, Alberto MCR, Butterbach-Bahl K, Kiese R
(Siehe online unter https://doi.org/10.1007/s10705-014-9658-1) - 2016, Greenhouse gas emissions and global warming potential of traditional and diversified tropical rice rotation systems. Global Change Biol. 22, 432-448
Weller S, Janz B, Jörg L, Kraus D, Racela HSU, Wassmann R, Butterbach-Bahl K, Kiese R
(Siehe online unter https://doi.org/10.1111/gcb.13099) - 2016, How well can we access impacts of agricultural land management changes on the total greenhouse gas balance (CO2, CH4 and N2O) of tropical rice-cropping systems with a biogeochemical model? Agric. Ecosys. Environm. 224, 104-115
Kraus D, Weller S, Klatt S, Santabárbara I, Haas E, Wassmann R, Werner C, Kiese R, Butterbach-Bahl K
(Siehe online unter https://doi.org/10.1016/j.agee.2016.03.037) - 2019, Greenhouse gas footprint of diversifying rice cropping systems: Impacts of water regime and organic amendments. Agriculture, Ecosystems and Environment 270–271, 41–54
Janz B, Weller S, Kraus D, Heathcliff SR, Wassmann R, Butterbach-Bahl K, Kiese R
(Siehe online unter https://doi.org/10.1016/j.agee.2018.10.011)
