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  • carbon dynamics  (3)
  • 1
    Electronic Resource
    Electronic Resource
    Using a Crop/Soil Simulation Model and GIS Techniques to Assess Methane Emissions from Rice Fields in Asia. I. Model Development (2000)
    Springer
    Nutrient cycling in agroecosystems 58 (2000), S. 141-159 
    Details
    ISSN: 1573-0867
    Keywords: methane ; rice ; Oryza sativa ; anaerobic ; model ; simulation ; carbon dynamics
    Source: Springer Online Journal Archives 1860-2000
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Notes: Abstract The development of the MERES (Methane Emissions in Rice EcoSystems) model for simulating methane (CH4) emissions from rice fields is described. The CERES-Rice crop simulation model was used as a basis, employing the existing routines simulating soil organic matter (SOM) decomposition to predict the amount of subsrate available for methanogenesis. This was linked to an existing submodel, described elsewhere in this volume (Arah & Kirk, 2000), which calculates steady-state fluxes and concentrations of CH4 and O2 in flooded soils. Extra routines were also incorporated to simulate the influence of the combined pool of alternative electron acceptors in the soil (i.e., NO3 −, Mn4+, Fe3+, SO4 2−) on CH4 production. The rate of substrate supply is calculated in the SOM routines of the CERES-Rice model from (a) the rate of decomposition of soil organic material including that left from the previous crop and any additions of organic matter, (b) root exudates (modified from the original CERES-Rice model using recent laboratory data), and (c) the decomposition of dead roots from the current crop. A fraction of this rate of substrate supply, determined by the concentration of the oxidized form of the alternative electron acceptor pool, is converted to CO2 by bacteria which outcompete the methanogenic bacteria, thereby suppressing CH4 production. Any remaining fraction of the substrate supply rate is assumed to be potentially available for methanogenesis. The CH4 dynamics submodel uses this potetial methanogenesis rate, along with a description of the root length distribution in the soil profile supplied by the crop model, to calculate the steady-state concentrations and fluxes of O2 and CH4. The reduced form of the alternative electron acceptor pool is allowed to reoxidize when soil pores fill with air if the field is drained. The MERES model was able to explain well the seasonal patterns of CH4 emissions in an experiment involving mid- and end-season drainage and additions of organic material at IRRI in the Philippines.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1009894619446
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  • 2
    Electronic Resource
    Electronic Resource
    Using a Crop/Soil Simulation Model and GIS Techniques to Assess Methane Emissions from Rice Fields in Asia. II. Model Validation and Sensitivity Analysis (2000)
    Springer
    Nutrient cycling in agroecosystems 58 (2000), S. 161-177 
    Details
    ISSN: 1573-0867
    Keywords: methane ; rice ; Oryza sativa ; anaerobic ; model ; simulation ; carbon dynamics
    Source: Springer Online Journal Archives 1860-2000
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Notes: Abstract The MERES (Methane Emissions from Rice EcoSystems) simulation model was tested using experimental data from IRRI and Maligaya in the Philippines and from Hangzhou in China. There was good agreement between simulated and observed values of total aboveground biomass, root weight, grain yield, and seasonal methane (CH4) emissions. The importance of the contribution of the rice crop to CH4 emissions was highlighted. Rhizodeposition (root exudation and root death) was predicted to contribute about 380 kg C ha−1 of methanogenic substrate over the season, representing 37% of the total methanogenic substrate from all sources when no organic amendments were added. A further 225 kg C ha−1 (22%) was predicted to come from previous crop residues, giving a total of around 60% originating from the rice crop, with the remaining 41% coming from the humic fraction of the soil organic matter (SOM). Sensitivity analysis suggested that the parameter representing transmissivity to gaseous transfer per unit root length (λr) was important in determining seasonal CH4 emissions. As this transmissivity increased, more O2 was able to diffuse to the rhizosphere, so that CH4 production by methanogens was reduced and more CH4 was oxidized by methanotrophs. These effects outweighed the opposing influence of increased rate of transport of CH4 through the plant, so that the overall effect was to reduce the amount of CH4 emitted over the season. Varying the root-shoot ratio of the crop was predicted to have little effect on seasonal emissions, the increased rates of rhizodeposition being counteracted by the increased rates of O2 diffusion to the rhizosphere. Increasing the length of a midseason drainage period reduced CH4 emissions significantly, but periods longer than 6–7 d also decreased rice yields. Organic amendments with low C/N were predicted to be more beneficial, both in terms of enhancing crop yields and reducing CH4 emissions, even when the same amount of C was applied. This was due to higher rates of immobilization of C into microbial biomass, removing it temporarily as a methanogenic substrate.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1009846703516
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  • 3
    Electronic Resource
    Electronic Resource
    Using a Crop/Soil Simulation Model and GIS Techniques to Assess Methane Emissions from Rice Fields in Asia. IV. Upscaling to National Levels (2000)
    Springer
    Nutrient cycling in agroecosystems 58 (2000), S. 201-217 
    Details
    ISSN: 1573-0867
    Keywords: rice ; model ; simulation ; carbon dynamics ; China ; India ; Indonesia ; Philippines ; Thailand ; estimates
    Source: Springer Online Journal Archives 1860-2000
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Notes: Abstract The process-based crop/soil model MERES (Methane Emissions from Rice EcoSystems) was used together with daily weather data, spatial soil data, and rice-growing statistics to estimate the annual methane (CH4) emissions from China, India, Indonesia, Philippines, and Thailand under various crop management scenarios. Four crop management scenarios were considered: (a) a 'baseline' scenario assuming no addition of organic amendments or field drainage during the growing season, (b) addition of 3,000 kg DM ha−1 of green manure at the start of the season but no field drainage, (c) no organic amendments but drainage of the field for a 14-d period in the middle of the season and again at the end of the season, and (d) addition of 3,000 kg DM ha−1 of green manure and field drainage in the middle and end of the season. For each scenario, simulations were made at each location for irrigated and rainfed rice ecosystems in the main rice-growing season, and for irrigated rice in the second (or 'dry') season. Overall annual emissions (Tg CH4 yr−1) for a province/district were calculated by multiplying the rates of CH4 emission (kg CH4 ha−1 yr−1) by the area of rice grown in each ecosystem and in each season obtained from the Huke and Huke (1997) database of rice production. Using the baseline scenario, annual CH4 emissions for China, India, Indonesia, Philippines, and Thailand were calculated to be 3.73, 2.14, 1.65, 0.14, and 0.18 Tg CH4 yr−1, respectively. Addition of 3,000 kg DM ha−1 green manure at the start of the season increased emissions by an average of 128% across the five countries, with a range of 74–259%. Drainage of the field in the middle and at the end of the season reduced emissions by an average of 13% across the five countries, with a range of −10% to −39%. The combination of organic amendments and field drainage resulted in an increase in emissions by an average of 86% across the five countries, with a range of 15–176%. The sum of CH4 emissions from these five countries, comprising about 70% of the global rice area, ranged from 6.49 to 17.42 Tg CH4 yr−1, depending on the crop management scenario.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1009850804425
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