The basic equation to estimate CH4 emissions from rice cultivation is shown in Equation 5.1. CH4 emissions are estimated by multiplying daily emission factors by cultivation period3 of rice and annual harvested areas4. In its
3 In the case of a ratoon crop, 'cultivation period' should be extended by the respective number of days.
most simple form, this equation is implemented using national activity data (i.e., national average cultivation period of rice and area harvested) and a single emission factor. However, the natural conditions and agricultural management of rice production may be highly variable within a country. It is good practice to account for this variability by disaggregating national total harvested area into sub-units (e.g., harvested areas under different water regimes). Harvested area for each sub-unit is multiplied by the respective cultivation period and emission factor that is representative of the conditions that define the sub-unit (Sass, 2002). With this disaggregated approach, total annual emissions are equal to the sum of emissions from each sub-unit of harvested area.
Equation 5.1 CH4 emissions from rice cultivation
CH4 Rice = Z (EFi, j,k • ti, j,k • Ai, j,k • 10 6) i, j,k
CH4 Rice = annual methane emissions from rice cultivation, Gg CH4 yr-1 EF ijk = a daily emission factor for i, j, and k conditions, kg CH4 ha-1 day-1 tijk = cultivation period of rice for i, j, and k conditions, day Ajk = annual harvested area of rice for i, j, and k conditions, ha yr-1
i, j, and k = represent different ecosystems, water regimes, type and amount of organic amendments, and other conditions under which CH4 emissions from rice may vary
The different conditions that should be considered include rice ecosystem type, flooding pattern before and during cultivation period, and type and amount of organic amendments. Other conditions such as soil type, and rice cultivar can be considered for the disaggregation if country-specific information about the relationship between these conditions and CH4 emissions are available. The rice ecosystem types and water regimes during cultivation period are listed in Table 5.12. If the national rice production can be subdivided into climatic zones with different production systems (e.g., flooding patterns), Equation 5.1 should be applied to each region separately. The same applies if rice statistics or expert judgments are available to distinguish management practices or other factors along administrative units (district or province). In addition, if more than one crop is harvested during a given year, emissions should be estimated for each cropping season taking into account possible differences in cultivation practice (e.g., use of organic amendments, flooding pattern before and during the cultivation period).
The decision tree in Figure 5.2 guides inventory agencies through the process of applying the good practice IPCC approach. Implicit in this decision tree is a hierarchy of disaggregation in implementing the IPCC method. Within this hierarchy, the level of disaggregation utilised by an inventory agency will depend upon the availability of activity and emission factor data, as well as the importance of rice as a contributor to its national greenhouse gas emissions. The specific steps and variables in this decision tree, and the logic behind it, are discussed in the text that follows the decision tree.
Tier 1 applies to countries in which either CH4 emissions from rice cultivation are not a key category or country-specific emission factors do not exist. The disaggregation of the annual harvest area of rice needs to be done for at least three baseline water regimes including irrigated, rainfed, and upland. It is encouraged to incorporate as many of the conditions (i, j, k, etc.) that influence CH4 emissions (summarized in Box 5.2) as possible. Emissions for each sub-unit are adjusted by multiplying a baseline default emission factor (for field with no preseason flooding for less than 180 days prior to rice cultivation and continuously flooded fields without organic amendments, EFc) by various scaling factors as shown in Equation 5.2. The calculations are carried out for each water regime and organic amendment separately as shown in Equation 5.1.
4 In case of multiple cropping during the same year, 'harvested area' is equal to the sum of the area cultivated for each cropping.
Conditions influencing CH4 emissions from rice cultivation
The following rice cultivation characteristics should be considered in calculating CH4 emissions as well as in developing emission factors:
Regional differences in rice cropping practices: If the country is large and has distinct agricultural regions with different climate and/or production systems (e.g., flooding patterns), a separate set of calculations should be performed for each region.
Multiple crops: If more than one crop is harvested on a given area of land during the year, and the growing conditions vary among cropping seasons, calculations should be performed for each season.
Water regime: In the context of this chapter, water regime is defined as a combination of (i) ecosystem type and (ii) flooding pattern.
Ecosystem type: At a minimum, separate calculations should be undertaken for each rice ecosystem (i.e., irrigated, rainfed, and deep water rice production).
Flooding pattern: Flooding pattern of rice fields has a significant effect on CH4 emissions (Sass et al., 1992; Yagi et al., 1996; Wassmann et al., 2000). Rice ecosystems can further be distinguished into continuously and intermittently flooded (irrigated rice), and regular rainfed, drought prone, and deep water (rainfed), according to the flooding patterns during the cultivation period. Also, flooding pattern before cultivation period should be considered (Yagi et al, 1998; Cai et al, 2000; 2003a; Fitzgerald et al, 2000).
Organic amendments to soils: Organic material incorporated into rice soils increases CH4 emissions (Schütz et al., 1989; Yagi and Minami, 1990; Sass et al, 1991). The impact of organic amendments on CH4 emissions depends on type and amount of the applied material which can be described by a dose response curve (Denier van der Gon and Neue, 1995; Yan et al, 2005). Organic material incorporated into the soil can either be of endogenous (straw, green manure, etc.) or exogenous origin (compost, farmyard manure, etc.). Calculations of emissions should consider the effect of organic amendments.
Other conditions: It is known that other factors, such as soil type (Sass et al, 1994; Wassmann et al, 1998; Huang et al, 2002), rice cultivar (Watanabe and Kimura, 1998; Wassmann and Aulakh, 2000), sulphate containing amendments (Lindau et al, 1993; Denier van der Gon and Neue, 2002), etc., can significantly influence CH4 emissions. Inventory agencies are encouraged to make every effort to consider these conditions if country-specific information about the relationship between these conditions and CH4 emissions is available.
Figure 5.2 Decision tree for CH4 emissions from rice production
Figure 5.2 Decision tree for CH4 emissions from rice production
1: See Volume 1 Chapter 4, "Methodological Choice and Identification of Key Categories" (noting Section 4.1.2 on limited resources), for discussion of key categories and use of decision trees.
EFj = adjusted daily emission factor for a particular harvested area
EFc = baseline emission factor for continuously flooded fields without organic amendments
SFw = scaling factor to account for the differences in water regime during the cultivation period (from Table 5.12)
SFp = scaling factor to account for the differences in water regime in the pre-season before the cultivation period (from Table 5.13)
SFo = scaling factor should vary for both type and amount of organic amendment applied (from Equation 5.3 and Table 5.14)
SFsr = scaling factor for soil type, rice cultivar, etc., if available
Tier 2 applies the same methodological approach as Tier 1, but country-specific emission factors and/or scaling factors should be used. These country-specific factors are needed to reflect the local impact of the conditions (i, j, k, etc.) that influence CH4 emissions, preferably being developed through collection of field data. As for Tier 1 approach, it is encouraged to implement the method at the most disaggregated level and to incorporate the multitude of conditions (i, j, k, etc.) that influence CH4 emissions.
Tier 3 includes models and monitoring networks tailored to address national circumstances of rice cultivation, repeated over time, driven by high-resolution activity data and disaggregated at sub-national level. Models can be empirical or mechanistic, but must in either case be validated with independent observations from country or region-specific studies that cover the range of rice cultivation characteristics (Cai et al, 2003b; Li et al, 2004; Huang et al, 2004). Proper documentation of the validity and completeness of the data, assumptions, equations and models used is therefore critical. Tier 3 methodologies may also take into account inter-annual variability triggered by typhoon damage, drought stress, etc. Ideally, the assessment should be based on recent satellite data.
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