Chapter 7: Wetlands

CHAPTER 7

WETLANDS

2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories

7.1

Volume 4: Agriculture, Forestry and Other Land Use

Authors
Catherine Ellen Lovelock (Australia), Christopher Evans (UK), Nathan Barros (Brazil), Yves Prairie (Canada),
Jukka Alm (Finland), , David Bastviken (Sweden), Jake J. Beaulieu (USA), Michelle Garneau (Canada), Atle
Harby (Norway), John Harrison (USA), David Pare (Canada), Hanne Lerche Raadal (Norway), Bradford Sherman(Australia), Chengyi Zhang (China), Stephen Michael Ogle (USA)Contributing Authors
Alistair Grinham (Australia), Bridget Deemer (USA), Marco Aurelio Santos (Brazil), Sarian Kosten (Netherlands),
Michael Peacock (Sweden), Zhe Li (China), Victor Stepanenko (Russian Federation)

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Chapter 7: Wetlands

Contents
7

Wetlands7.6
7.1

Introduction ......................................................................................................................................... 7.6

7.2

Managed Peatlands.............................................................................................................................. 7.6

7.3

Flooded Land ...................................................................................................................................... 7.6
7.3.1 Flooded Land Remaining Flooded Land ..................................................................................... 7.11
7.3.2 Land Converted to Flooded Land ................................................................................................ 7.20
7.3.3 Approach to provide indicative estimates of the anthropogenic component of total CO2 and nonCO2 emissions (optional) ............................................................................................................. 7.26
7.3.4 Uncertainty Assessment .............................................................................................................. 7.28

7.4

Completeness, Times Series Consistency, and QA/QC .................................................................... 7.29

7A.1.1

Background on CH4 cycling in Flooded Land .................................................................................. 7.30

7A.1.2

Reservoirs.......................................................................................................................................... 7.32

7A.1.3

Other constructed waterbodies (agricultural ponds, aquaculture ponds, canals and ditches) ............ 7.43

Equations
Equation 7.10 (New)Annual total CH4 emissions for Reservoirs >20 years old (Flooded Land Remaining
Flooded Land) ............................................................................................................ 7.12

Equation 7.11 (New)

Equation used to scale CH4 emission factors for the influence of eutrophication using
measured values of chlorophyll a (Modified from Deemer et al. 2016) ..................... 7.13

Equation 7.12 (New)Annual CH4 emission from Other Constructed Waterbodies ...................................... 7.17

Equation 7.13 (New)Annual on-site CO2-c emissions/removals from land converted to flooded land ....... 7.21

Equation 7.14 (New)Annual CO2-C emissions/removals from Land Converted to Flooded Land including
soil carbon stocks........................................................................................................ 7.21

Equation 7.15 (New)Annual CH4 emissions for Reservoirs ≤ 20 years old for Land Converted to Flooded
Land ............................................................................................................................ 7.25

Equation 7.16 (New)

Indicative estimate of the anthropogenic component of total annual CH4 emissions inFlooded Land Remaining Flooded Land .................................................................... 7.27

Equation 7.17 (New)

Indicative estimate of the anthropogenic component of total annual CO2 emissions inland converted to flooded land ................................................................................... 7.27

Equation 7.18 (New)

Indicative estimates of the anthropogenic component of total annual CH4 emissions inLand Converted to Flooded Land ............................................................................... 7.28

Equation 7A.1 (New)CH4 diffusive emission (Mg C m-2 d-1) ....................................................................... 7.33

Equation 7A.2 (New)CH4 bubbling emission (Mg C m-2 d-1) ...................................................................... 7.33

Equation 7A.3 (New)CO2 diffusive emission (Mg C m-2 d-1) ....................................................................... 7.34

Equation 7A.4 (New)

Emission Factors for Land converted to Flooded Land .............................................. 7.36

Equation 7A.5 (New)

Emission factors for Flooded Land remaining Flooded Land .................................... 7.36

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FiguresFigure 7.2 (New)

Decision tree for types of Flooded Land. ................................................................... 7.10

Figure 7.3 (New)

Decision tree for choice of Tier level to estimate emissions of CO2 and CH4 fromwaterbodies ................................................................................................................. 7.11

Figure 7A.1 (New)Methane related transport within and from waterbodies, exemplified with a reservoir
with an anoxic hypolimnion ....................................................................................... 7.31

Figure 7A.2 (New)

Location of the reservoirs in the GranD database and shadowgram of their latitudinal
distribution. ................................................................................................................. 7.35

Figure 7A.3 (New)Box plots of model estimates (empty) and Field measurements (filled) of CH4 emissions(note logarithmic scale) in aggregated IPCC climate zones. ...................................... 7.38

Figure 7A.4 (New)Comparison of measure CH4 emissions with estimates based on the Emission Factors(EFs, Tables 7.9 and 7.15) of Tier 1 methodology. .................................................... 7.39

Figure 7A.5 (New)Measured downstream (DN) CH4 emissions compared to model estimates. .............. 7.40

Figure 7A.6 (New)

Relationship between CO2 surge estimates from the newly flooded lands using the
decay curve approach and the flooded soil organic carbon stock approach. .............. 7.41

TablesTable 7.7 (New)Types of Flooded Land, their human uses and greenhouse gas emissions considered inthis chapter.................................................................................................................... 7.6

Table 7.8 (New)Ramsar classes of human-made wetlands, IPCC terminology used and methodologicalguidance provided......................................................................................................... 7.8

Table 7.9 (New)CH4 emission factors for reservoirs older than 20 years (> 20 years) – Flooded Land
Remaining Flooded Land ........................................................................................... 7.15

Table 7.10 (New)

Ratio of total downstream flux of CH4 (kg CH4 ha -1 yr-1) to the flux of CH4 from areservoir’s surface to the atmosphere (kg CH4 ha -1 yr-1) – Rd .................................... 7.15

Table 7.11 (New)

Relationships between Trophic Index (TI), surface concentrations of chlorophyll-a (Chla), total phosphorus (TP), total nitrogen (TN), Secchi depth (SD), and Trophic Class1
and Trophic State Adjustment Factor (αi) .................................................................. 7.15

Table 7.12 (New)CH4 emission factors for Other Constructed Waterbodies (freshwater ponds, saline
ponds, canals, drainage channels and ditches) ............................................................ 7.18

Table 7.13 (New)

CO2-C emission factors for reservoirs ≤ 20 years old – Land converted to Flooded Land.................................................................................................................................... 7.23

Table 7.14 (New)

Scaling factor value M [y-1] for equation 7.14, Annual on-site CO2-C
emissions/removals from Land Converted to Flooded Land. ..................................... 7.24

Table 7.15 (New)CH4 emission factors for reservoirs ≤ 20 years old – Land converted to Flooded Land.................................................................................................................................... 7.26

Table 7A.1 (New)

Number of reservoirs in the Grand database in each IPCC climate zone. .................. 7.35

Table 7A.2 (New)

Aggregated climate zones based on differences in CH4 emissions between categories.................................................................................................................................... 7.37

Table 7A.3 (New)Data sources used for modelling CH4 emissions from reservoirs within different climate
zones. .......................................................................................................................... 7.42

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Chapter 7: Wetlands

Table 7A.4 (New)Reservoirs and citations for measured Rd values ........................................................ 7.43

Boxes
Box 7.1 (New)

Additional information on sedimentation and carbon burial in reservoirs.................. 7.14

Box 7.2 (New)

Additional information on emissions arising from wastewater within reservoirs....... 7.16

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7

WETLANDS

7.1

INTRODUCTION

No refinement.

7.2

MANAGED PEATLANDS

No refinement.

7.3

FLOODED LAND

Flooded Lands are defined in the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (Wetlands) as
water bodies where human activities have caused changes in the amount of surface area covered by water,
typically through water level regulation. Here, we also consider: i) waterbodies where human activities havechanged the hydrology of existing natural waterbodies thereby altering water residence times and/or sedimentation
rates, in turn causing changes to the natural flux of greenhouse gases (See A7.1.1); and ii) waterbodies that havebeen created by excavation, such as canals, ditches and ponds. Flooded Lands include waterbodies with seasonallyvariable degrees of inundation but would be expected to retain some inundated area throughout the year undernormal conditions. Seasonally flooded wetlands such as riparian floodplain wetlands are not considered here;
where these have been modified by human activity, emissions may be estimated using the methods described in
the 2013 Supplement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories: Wetlands (2013
Wetlands Supplement, (IPCC 2014)). The range of Flooded Land considered in this chapter are listed in Table 7.7.
TABLE 7.7 (NEW)TYPES OF FLOODED LAND, THEIR HUMAN USES AND GREENHOUSE GAS EMISSIONS CONSIDERED IN THIS CHAPTER
Flooded Land types

Human Uses

Greenhouse gas emissions
for which guidance isprovided in this Chapter

Reservoirs (including open water,
drawdown zones, anddegassing/downstream areas)

Hydroelectric Energy Production, FloodControl, Water Supply, Agriculture,
Recreation, Navigation, Aquaculture

CO2, CH4

CanalsWater Supply, Navigation

CH4

Ditches

Agriculture (e.g. irrigation, drainage,and livestock watering)

CH4

Ponds (Freshwater or Saline)

Agriculture, aquaculture, recreation

CH4

Flooded Land emits CO2, CH4 and N2O in significant quantities, depending on a variety of characteristics such asage, land-use prior to flooding, climate, upstream catchment characteristics and management practices. Emissions
vary spatially and over time.
CO2 emissions
Emissions of CO2 from Flooded Land remaining Flooded Land are primarily the result of decomposition of soilorganic matter and other organic matter within the waterbody or entering the waterbody from the catchment, as
well as respiration of biota (e.g. bacteria, macroinvertebrates, plants, fish, and other aquatic species). No guidanceis provided in this section for emissions associated with decomposition of organic matter delivered from thecatchment or respiration of biota because they are either accounted for elsewhere in the estimation methods(Volume 4, Chapter 4, Forest Land, CO2 emissions from soils Section 4.2.3, Chapter 5, Croplands, CO2 emission
from soils, Section 5.2.3) or reflect short-term carbon cycling by the aquatic biota. The one exception is for Land
Converted to Flooded Lands. CO2 emissions occur as the flooded organic matter decomposes, which is aconsequence of anthropogenic management, and methods are provided for estimating the resulting CO2 emissions(Section 7.3.2.1).
CH4 emissions
Emissions of CH4 from Flooded Land are primarily the result of CH4 production induced by anoxic conditions inthe sediment (see Annex 7.1). Methane can be emitted from small lakes or reservoirs via diffusive, ebullitive, anddownstream emissions. Downstream CH4 emissions are subdivided into degassing emissions (see Glossary) and7.6

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Chapter 7: Wetlands

diffusive emissions, which occur downstream from the flooded land. Methane emissions are generally higher inwaterbodies with high organic matter loading and/or high internal biomass production, and low oxygen status.
Due to their high emission rates and large numbers, small ponds of area < 0.1 ha have been estimated to generate
40 percent of diffusive CH4 emissions from open waters globally (Holgerson & Raymond 2016). Whilst emissions
from natural ponds can (at least in part) be considered natural, those from small constructed waterbodies are theresult of anthropogenic activity. High organic loadings and low oxygen levels can also occur in drainage ditches(Evans et al. 2016), constructed ponds for agriculture (e.g. (Selvam et al. 2014) aquaculture (Avnimelech & Ritvo
2003), and flooded pastures (Kroeger et al. 2017). Emission rates of CH4 from small constructed waterbodies
where nutrient loadings from agriculture or other sources are high may exceed those from small natural
waterbodies, (Tangen et al. 2015), (Yang et al. 2017), and may equal or exceed those observed in small lakes andreservoirs (Bastviken et al. 2011). Emissions of CH4 from aquaculture ponds may be reduced through aquaculture
management, including mixing or aeration, periodic drainage or when water is saline (Vasanth et al. 2016), (Yanget al. 2017), (Robb et al. 2017). Because CH4 emissions from constructed waterbodies can be considered a directconsequence of the construction of the waterbody, guidance on reporting these emissions is provided in this chapter.
Nitrous oxide emissions
Nitrous oxide emissions from Flooded Lands are largely related to input of organic or inorganic nitrogen from thewatershed. These inputs from runoff/leaching/deposition are largely driven by anthropogenic activities such as
land-use change, wastewater disposal or fertilizer application in the watershed or application of fertilizer or feedin aquaculture. The current section does not consider these emissions in order to avoid double-counting of N2Oemissions, which are already captured in other source categories, such as indirect N2O emissions from managed
soils (see Volume 4, Chapter 11) and wastewater management (see Volume 5, Chapter 6). Nitrous oxide emissions
from aquaculture ponds constructed on coastal wetlands are given in Chapter 4 of the 2013 Supplement Chapter 4,
Section 4.3.2). Compilers may address local sources of N2O emissions (i.e. those not driven by external inputs ofN) using Tier 2 or Tier 3 methods.

TYPES OF FLOODED LANDS
Reservoirs
Reservoirs are designed to store water over time scales ranging from hours to several years. Their use can serve
single (e.g. water supply) or multiple purposes, and reservoir operation may vary depending on different user needs(Table 7.7). Hydropower reservoirs can be divided in three categories: storage, run-of-the-river and pumped
storage reservoirs. These categories generally describe the relationship between storage volume, inflow and water
residence times, but in reality, reservoirs exist on a spectrum. Natural lakes may also be used as reservoirs, often
by damming to expand their volume and surface area.
Flooded land is exposed to natural or anthropogenic regulation of water levels, creating a drawdown zone.
Greenhouse gas emissions from the drawdown zones are considered significant and similar per unit area to theemissions from the water surface (e.g. (Yang et al. 2012), (Deshmukh et al. 2018)) and are therefore included
when estimating greenhouse gas emissions from Flooded Land. Lakes converted into reservoirs without substantialchanges in water surface area or water residence times are not considered to be managed Flooded Land, in
accordance with the 2006 IPCC Guidelines.
Reservoirs are classified according to the length of time they have been flooded:(i) Flooded Land Remaining Flooded Land – includes reservoirs that were converted to Flooded Land morethan 20 years ago.
(ii) Land Converted to Flooded Land – includes reservoirs that were flooded less than or equal to 20 years ago.

Other Flooded Land: Constructed ponds, canals, ditches and flooded pastures
Ponds are constructed by excavation and/or construction of walls to hold water in the landscape for a range of uses,
including agricultural water storage, access to water for livestock, recreation, and aquaculture. They often receive
high organic matter and nutrient loadings, may have low oxygen levels, and are sites of substantial CH4 emissions
from anaerobic sediments. However, because seawater suppresses production of CH4, emissions from saline
aquaculture ponds are lower compared to freshwater ponds. Constructed linear waterbodies (which we define herein accordance with the Ramsar Convention category of ‘Human-made wetlands: Canals and drainage channels
or ditches’) are also extensive in many agricultural, forest and settlement areas, and may also be significant sourcesof emissions in some circumstances. For CH4 emissions from Other Flooded Land, there are insufficient data to
disaggregate based on age classes of the waterbodies.

Flooded Land Excluded Here, But Considered Elsewhere
Emissions from various kinds of Flooded Land that are not considered in this chapter are provided in the 2013
Wetlands Supplement and in other parts of this guidance. Table 7.8 provides the Ramsar classification, which2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories

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Volume 4: Agriculture, Forestry and Other Land Use

provides the framework for the terminology used in this guidance. Some rice paddies are cultivated throughflooding of land, but because of the unique characteristics of rice cultivation, rice paddies are addressed in Volume
4, Chapter 5 (Cropland). Emissions from wetlands created or used for wastewater treatment are provided in
Chapter 6 of the 2013 Wetlands Supplement (Constructed Wetlands for Waste Water Treatment). Seasonally
flooded agricultural land (including intensively managed or grazed wet meadow or pasture) that is formed via
human modification of natural hydrological processes may also be considered Flooded Land, and can be asignificant source of CH4 emissions (Kroeger et al. 2017). Seasonally flooded agricultural land may be coastal orinland, on mineral or organic soils, and relevant guidance for CO2 emissions and removals from these categories
is provided in the 2013 Wetlands Supplement (Chapters 3-5, see Table 7.8 for details). CO2 emissions associatedwith construction of aquaculture ponds in coastal wetlands are also considered in the 2013 Wetlands Supplement(Section 4.2.4 and Section 4.3.2). Flooding of land to create wetlands in coastal settings due to management
activities, such as breaching of sea defences, are found under "rewetting" within the 2013 Wetlands Supplement(Section 4.2.3 for CO2 and 4.3.1 for CH4). Constructed seawater canals are not considered because there areinsufficient data to derive an emission factor. Furthermore, water in seawater canals is assumed to have salinity
greater than 18 ppt, and therefore will have no CH4 emissions, consistent with guidance in the 2013 Wetlands
Supplement.
TABLE 7.8 (NEW)RAMSAR CLASSES OF HUMAN-MADE WETLANDS, IPCC TERMINOLOGY USED AND METHODOLOGICAL GUIDANCEPROVIDEDRAMSAR class1

Corresponding wetlands subcategories in IPCC Chapters

Methodological guidance available?

Water storage areas

Reservoir

Yes for CH4 and CO2 (this chapter)

Ponds

Other constructed waterbodies

Yes for CH4 and CO2 (this chapter)

Canals and drainage channels
or ditches.

Other constructed waterbodies

Yes for CH4 and CO2 (this chapter)Yes for CH4 in peatlands (2013
Wetlands Supplement, Chapter 2)

Aquaculture

Other constructed waterbodies

Yes for CH4 and CO2 (this chapter)Yes for CO2 during construction andfor N2O (2013 Wetlands Supplement,
Chapter 4)2

Irrigated land (if cultivated)

CroplandYes (Vol. 4, Chapter 5)

Seasonally flooded agricultural
land

Rice Cultivation

Yes (Vol. 4, Chapter 5)

Seasonally flooded agriculturalland including intensively
managed or grazed wet
meadow or pasture

Wetlands

Yes for CH4 (2013 Wetlands
Supplement, Chapters 3, 4 and 5)3,4

Salt exploitation sites

Wetlands

Yes (2013 Wetlands Supplement,
Chapter 4)

Excavations (partly)

Peatlands managed for peat extraction

Yes (2013 Wetlands Supplement,
Chapter 2)

Wastewater treatment areas“Constructed wetlands” or Waste Sector

Yes (2013 Wetlands Supplement,
Chapter 6; Volume 5, Chapter 6)

NOTES:
1

Source: (Ramsar 2014)2

2013 Wetlands Supplement, Chapter 4, Section 4.3.2 for N2O

3 2013 Wetlands Supplement Chapter 3 for guidance on rewetted organic soils (Section 3.2.1 for CO , Section 3.2.2. for CH2
4 andSection 3.2.3 for N2O); Chapter 4 for guidance for seasonally flooded agricultural land on land that was previously coastal wetlands(Section 4.2.3 for CO2; Section 4.3.1 for CH4) and Chapter 5 for seasonally flooded agricultural land on inland mineral soils (Section
5.2.1 for CO2 and 5.2.2 CH4)
4

Including permanently flooded lands associated with rewetting of converted wetlands

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Chapter 7: Wetlands

CHOICE OF METHOD, ACTIVITY DATA AND EMISSION FACTORS
Guidance is provided for choice of methods, activity data and emission factors for Flooded Land Remaining
Flooded Land (Reservoirs > 20 years old) and other constructed waterbodies, and for Land Converted to Flooded
Land (Reservoirs ≤ 20 years old). Guidance for selecting the type of waterbody based on human modification,hydrology (where there has been a significant change in surface area, and/or residence time, by > 10 percent),
water quality, size and function and associated emission factors and activity data is presented in the decision tree
in Figure 7.2. Tier selection and the level of spatial and temporal disaggregation will depend upon the availabilityof activity data and emission factors, as well as the importance of Flooded Land as an emission source based on
the key category analysis for a country’s national greenhouse gas inventory. Figure 7.3 provides a decision tree toselect the appropriate tier level for estimating emissions from Flooded Land. Country-specific emission factors
and data are generally preferable to Tier 1 default data.
Conversion of unmanaged waterbodies and unmanaged wetlands to managed Flooded Lands
Greenhouse gas emissions (removals) occur on unmanaged land prior to conversion into managed land for both
Flooded Land remaining Flooded Land and Land converted to Flooded Land. The anthropogenic impact ongreenhouse gas emissions from managed flooded land reflect the net changes in greenhouse gas fluxes to theatmosphere resulting from the landscape transformation into a reservoir or other flooded lands (Prairie et al. 2017a).
Indicative estimates of the anthropogenic component of the total greenhouse gas emissions occurring on the
Flooded Land (see Annex Box A1) may optionally be estimated, in addition to the total emissions. This estimate
may be obtained for Land Converted to Flooded Land by estimating emissions from the area of Managed Lands
and Other Unmanaged Lands converted to managed Flooded Land. Types of Unmanaged Land converted to
Flooded Land include: 1) unmanaged lakes and rivers (collectively termed ‘unmanaged waterbodies’) expandedby dam construction; 2) Unmanaged Wetlands (excluding lakes and rivers) converted to Flooded Land; and 3)
Other Unmanaged Lands (including Unmanaged Forest Land, Grassland and Other Land). Previously flooded
lands where changes in hydrology lead to substantial changes in the characteristics and ecological function of thearea, or emissions and removals per unit area, may not be excluded from the calculation of indicative estimates of
the anthropogenic component of total greenhouse gas emissions.
Emissions from Unmanaged Wetlands converted to Flooded Lands are considered part of the non-anthropogenic
component of the emissions for the first 20 years, after which they are considered to function similarly to thereservoir as a whole. This is the result of the legacy of the natural wetland function which will gradually transition
to the condition of the surrounding reservoir as the accumulated organic matter is decomposed or buried in thereservoir. The method to produce indicative estimates of the anthropogenic component of total greenhouse gas
emissions is presented separately in Section 7.3.3.
The methods provided in this section are scientifically-based but with practical consideration for application of themethods by compilers. It is good practice for the greenhouse gas emissions in the AFOLU sector to be estimatedusing the Managed Land Proxy (MLP), in which all emissions from managed land are considered anthropogenic,
and to provide details of the methodology used (See Chapter 3, Volume 4). Therefore, for transparency, themethods are applied so that the total emissions from flooded lands are estimated based on the MLP, whileemissions that are specifically to be the result of human activity within these areas are estimated by calculating theemissions for the area of Managed Land and Other Unmanaged Land converted to Flooded Land. For thosecountries that choose to develop indicative estimates of the anthropogenic component of total greenhouseemissions, it is good practice to report the MLP emissions, as well as the indicative estimates of the anthropogenic
component of total greenhouse gas emissions. Details of the methodology used should be documented. As withother sources, Tier 1 methods have large uncertainties that may be reduced with development of Tier 2 or 3
methods.

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Figure 7.2 (New)

Decision tree for types of Flooded Land.
Start

Is this anatural waterbody that has been
modifiedNo

Not Flooded land
Stop

Is there a significant(≥10% or 0.25 ha) increase insurface area?

No

Is a constructed waterbody?

No

Yes

Yes

Has the storage volume, inflow, or
residence times changed
significantly?

No
Yes

Is inundated land an
artificially constructed linear
waterbody (ditch, drain,
canal)?

Yes

Yes

No

Yes

Is surface area < 8 ha?

No

Yes

Is the main use foraquaculture?

No
Is the main use forhydropower?

Yes

Reservoir
Yes

Yes

Other constructed water
body

7.10

Land Converted to
Flooded land

Is the reservoir ≤ 20
years old?

No

Flooded Land Remaining
Flooded land2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories

Chapter 7: Wetlands

Figure 7.3 (New)

Decision tree for choice of Tier level to estimate emissions of CO 2 andCH 4 from waterbodies
Start

Estimate emissions using Tier
1 equations

Are waterbodies a key category?

No

Use Tier 1 emission equations
Box1: Tier 1

Yes

Are there
country-specific emission
factors, models, ormeasurement-based
approaches?

No

Yes
Yes

Are there sufficient data and resources to develop
country-specific emission actors, and/or test amodel, or a measurement-based monitoring
approach?

No

7.3.1

Estimate emissions using
country-specific emission
factors or Tier 3 methods

Estimate emissions using
Tier 1 default emission factor
valuesBox3: Tier 3

Box2: Tier 1

Flooded Land Remaining Flooded Land7.3.1.1 T OTAL CO 2 EMISSIONS FROM F LOODED L AND R EMAININGF LOODED L AND
The initial flooding of land can cause elevated CO2 emissions as inundated soil and biomass decay. After thisinitial phase, typically lasting 20 years or less, the CO2 emitted from Flooded Land is largely derived from carbon
input from the catchment, which is estimated as emissions from other managed land categories, and not addressedin this category to avoid double-counting of emissions (i.e., Volume 4, Chapter 4 Forest Land, Chapter 5 Cropland,
Chapter 6 Grassland, Chapter 8 Settlements and the 2013 Wetlands Supplement). Therefore, no methodologies(Choice of Methods, Emission Factors, or Activity Data) are provided to estimate total CO2 emissions for Flooded
Land Remaining Flooded Land.

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7.3.1.2 T OTAL N ON -CO 2 EMISSIONS FROM F LOODED L AND
REMAINING F LOODED L AND
RESERVOIRS
Choice of Method
The following methodology is provided for estimating CH4 emissions from reservoirs more than 20 years old. The
Tier 1 methodology allows the estimation of the total diffusive, ebullitive and downstream CH4 emissions (seeGlossary), FCH4tot, (Equation 7.10).
If sufficient data exist, it is good practice for the compiler to develop country-specific emission factors using a
Tier 2 or Tier 3 method to reduce overall uncertainty. Guidance on the development of country-specific factors
and methods is provided below in the Tier 2 and 3 sections. For reservoirs less than 20 years old, see section
7.3.2.3, Land Converted to Flooded Lands.

Tier 1
Total emissions from flooded land (FCH4tot) is the sum of the emissions occurring at the surface of the reservoir(FCH4res) and those originating within the reservoir but occurring downstream of the dam (FCH4downstream):
EQUATION 7.10 (NEW)
ANNUAL TOTAL CH4 EMISSIONS FOR RESERVOIRS >20 YEARS OLD (FLOODED LAND REMAINING
FLOODED LAND)F=
FCH 4 res + FCH 4 downstream
CH 4tot
6 nres j

FCH4res = ∑ ∑ αi (EFCH 4 age>20, j • Atot j,i )

(A)
(B)

=j 1 =i 1

6 nres j

FCH 4 downstream = ∑ ∑ αi (EFCH 4 age>20, j • Atot j,i )• Rd, i(C)=j 1 =i 1

Where:

FCH 4tot= Total annual emission of CH4 from all reservoirs > 20 years old, kg CH4 yr-1

FCH 4 res= Annual reservoir surface emissions of CH4 from all reservoirs > 20 years old, kg CH4 yr-1

FCH 4 downstream = Annual emissions of CH4 originating from all reservoirs but emitted downstream of dam,kg CH4 yr-1. For Tier 1, equation 7.10 (C) simplifies to FCH 4 downstream = FCH4res • Rd

Atot j,i= Total area of reservoir water surface for reservoir > 20 years old 'i' located in climate zone
'j', ha

EFCH 4 age>20, j = Emission factor for CH4 emitted from the reservoir surface for reservoir > 20 years old
located in climate zone 'j', kg CH4 ha-1 yr-1 (Table 7.9).

7.12

Rd

= A constant equal to the ratio of total downstream emission of CH4 to the total flux of CH4
from the reservoir surface [dimensionless]. Equals 0.09 by default for Tier 1 (Table 7.10).
See text below for Tiers 2 & 3 Rd values.

αi= Emission factor adjustment for trophic state in reservoir i within a given climate zone.
[dimensionless] Equals 1.0 by default for Tier 1. See Equation 7.11 for Tiers 2 & 3.

i

= Summation index for the number of all reservoirs > 20 years in climate zone 'j'j= Summation index for climate zones (j = 1-6, see Table 7.9)

nres j= Number of reservoirs > 20 years old in climate zone ‘j’2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories

Chapter 7: Wetlands

The equation for scaling CH4 emission factors for eutrophication is estimated as follows:
EQUATION 7.11 (NEW)EQUATION USED TO SCALE CH4 EMISSION FACTORS FOR THE INFLUENCE OF EUTROPHICATIONUSING MEASURED VALUES OF CHLOROPHYLL A (MODIFIED FROM DEEMER ET AL. 2016)=
α i 0.26 • Chlai
Where:

αi= Emission factor adjustment for trophic state in reservoir 'i', dimensionless. Equals 1.0 for
Tier 1.

Chlai= Mean annual chlorophyll-a concentration in reservoir 'i', µg L-1

When chlorophyll values are not available, the trophic state adjustment factor (αi, Eq. 7.11) can be estimated fromother general assessments of reservoir trophic status (See Table 7.11).

Tier 2At the Tier 2 level, downstream emissions can be estimated based on water withdrawal depths for individual
reservoirs. If water is withdrawn from the oxic (upper) part of the water column, the CH4 content of the water is
expected to be relatively low, therefore downstream emissions can be assumed to be zero. If water is withdrawn
from the anoxic (lower) part of the water column, where dissolved CH4 can accumulate to high levels, downstream
emissions should be estimated following equation 7.10 using the Rd factor found in Table 7.10 or by a Tier 3
methodology.
If a country has characterized the trophic status of its reservoirs, a compiler can improve estimates of CH4
emissions from these systems by multiplying default CH4 emission factors (from Table 7.9) by a factor, αi, either
computed from measured mean annual chlorophyll-a (Chl-a) data using Equation 7.11, or taken from Table 7.11
where trophic state may be known but mean annual Chl-a data are lacking. Equation 7.10 generally provides amore accurate approach where reservoir Chl-a concentrations [Chl-a] have been measured. If sufficient data are
available locally to determine a country-specific relationship between trophic status and CH4 fluxes, then local
values should be used in Equation 7.10 rather than these global averages.
Where there are sufficient data, compilers may also include the effect of carbon burial in the sediments in casethere is a net removal of carbon in the managed flooded land (see Box 7.1).

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BOX 7.1 (NEW)ADDITIONAL INFORMATION ON SEDIMENTATION AND CARBON BURIAL IN RESERVOIRS

Reservoirs are often sites of significant accumulation of sediments, and therefore carbon (Clow etal. 2015). However, to consider such carbon accumulation as an offset to greenhouse gas emissions
is complex because it depends strongly on the origin of the sediments and what the fate of theassociated carbon would have been in the absence of a reservoir (Prairie et al. 2017a). For example,
particulate organic carbon from the upstream catchment sediments would, prior to impoundment,
have been transported and possibly stored further downstream. Only the net additional C storage
induced by the sediment trapping within the reservoir would constitute removal. Similarly, if carbon
burial is the result of autochthonous (inside the reservoir) primary production by algae or aquaticplants, such carbon removal would necessarily be reflected in the CO2 exchange occurring at the airwater interface. Subtracting C sedimentation from the air-water exchange would thus lead to adouble-counting of the same carbon flux. Lastly, in many reservoirs, maintenance operations involvethe sluicing of excess sediments to the downstream river by opening gates located at the base of thedam, thereby releasing unknown, but often large, amounts of accumulated sediment carbon over ashort period.
As a result of the processes described above and the difficulties in quantifying them, a Tier 1
methodology cannot be developed for the reporting of sediment carbon accumulation. For thedevelopment of higher Tier methodologies for carbon accumulation in reservoirs, an important
guiding principle is that only the portion of the carbon permanently buried in reservoir sedimentsthat would not have been stored elsewhere in the hydrological network (lakes, rivers, wetlands andthe coastal ocean) could potentially be considered as an additional carbon burial in the anoxic
sediment of the reservoir (Isidorova et al. 2019) .

Tier 3
Direct measurements of CH4 diffusion and ebullition fluxes across the reservoir surface provide the most accuratealternative to the Tier 1 and Tier 2 approaches. It is good practice to undertake measurements at sufficient different
locations and sufficient different times of year to capture both the spatial and temporal variability of CH4 emissions
from a reservoir (see UNESCO/IHA GHG Measurement Guidelines for Freshwater Reservoirs 2010 (Goldenfum2010) for additional guidance). CH4 emissions are often highly spatially variable, with 50-90 percent of totalreservoir emissions emanating from 10-30 percent of a reservoir’s surface (typically in areas subject to highorganic matter deposition such as the distal arms receiving significant catchment inflows (Sherman et al. 2012)).
Degassing can be estimated as the difference between the dissolved gas concentration at the water entering thedam and the dissolved gas concentration downstream of the dam, multiplied by the outlet discharge. Dissolved
gas concentration of the water entering the dam can be estimated from water samples collected from the reservoir
at the depth of the water intake or directly from the water conveyance structure, if possible. Diffusive emission
from the downstream river can be directly measured or estimated using a mass balance approach. See (Goldenfum2010) (UNESCO/IHA), section 2.4.1.2.3).
Accuracy is improved when measurements are undertaken across a full seasonal cycle because CH4 dynamics arevery temperature sensitive. The accuracy of CH4 emissions can also be improved by considering atmospheric andhydrostatic pressure that may strongly influence CH4 ebullition. The measurement data should be area-weighted
and seasonally averaged to provide the most accurate estimate of emissions from the reservoir as a whole (SeeAnnex 7.1 for details).
CH4 emissions from individual reservoirs can also be estimated by application of the Greenhouse Gas Reservoir
Tool (G-res) model (Prairie et al. 2017b), with reservoir-specific data covering: reservoir morphometry, littoral areas,
and local climate data including temperature and solar radiation. G-res is described in more detail in Annex 7.1.
Other detailed models could be developed that include the range of environmental and management conditions
that influence emissions (see Annex 7.1).

Choice of Emission Factors
Tier 1
Emission factors for CH4 via diffusion and ebullition from the reservoir surface, EFCH4 age>20,j in the six aggregatedclimate zones are provided in Table 7.9. The emission factors integrate both spatial and temporal variations andhave been derived from the application of empirical models to a large number of reservoirs (>6000) with aworldwide distribution and are averaged per climate zone. See Annex 7.1 for details of how default emissions
factors were derived.

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Chapter 7: Wetlands

TABLE 7.9 (NEW)CH4 EMISSION FACTORS FOR RESERVOIRS OLDER THAN 20 YEARS (> 20 YEARS) – FLOODED LAND REMAINING FLOODED
LAND
Aggregated Climate Zone

CH4 Emission Factors EFCH4 age>20,j(kg CH4 ha-1 year-1)
jAverage

Lower and upper 95% CI of mean

N

Boreal1

13.6

7.3-19.996

Cool Temperate

2

54.0

48.3-59.5

1879

Warm temperate/dry

3

150.9

133.3-168.1

578

Warm temperate/moist

4

80.3

74.0-86.0

1946

Tropical dry/montane

5

283.7

261.9-305.8

710

Tropical moist/wet

6

141.1

131.1-152.7

805

The emission factors are derived from the G-Res model outputs from N reservoirs in each climate zone. The aggregation into 6 climate
zones is described in Annex 1, section A7.1.2.1. N is the number of modelled reservoirs used to estimate EF values and their 95%
confidence intervals.

Default values for the ratio of total downstream emission of CH4 to the total flux of CH4 from the reservoir surface
are provided in Table 7.11.
TABLE 7.10 (NEW)RATIO OF TOTAL DOWNSTREAM FLUX OF CH4 (KG CH4 HA -1 YR-1) TO THE FLUX OF CH4 FROM A RESERVOIR’S SURFACE
TO THE ATMOSPHERE (KG CH4 HA -1 YR-1) – RDMedianUpper 95% CI of themedianLower 95% CI of themedianNumber of reservoirs

0.09

0.22

0.05

36

Note: The default Tier 1 value is the median of all Rd values reported in the literature. The 95% confidence interval of the median was
calculated using the bias-corrected and accelerated (BCa) bootstrap interval.
References: (Teodoru et al. 2012), (Diem et al. 2012), (DelSontro et al. 2016), (Maeck et al. 2013), (Soumis et al. 2004), (Beaulieu et al.
2014a), (Bevelhimer et al. 2016), (Descloux et al. 2017), (DelSontro et al. 2011), (dos Santos et al. 2017), (Kumar & Sharma 2016),(Chanudet et al. 2011), (Abril et al. 2005), (Bastien & Demarty 2013), (Deshmukh et al. 2016), (Serça et al. 2016), (Guérin et al. 2006),(Kemenes et al. 2007).

Trophic state adjustment factor (αi, Eq. 7.11) can be estimated from other general assessments of reservoir trophic
status, for example from trophic index, total phosphorus and nitrogen and Secchi depth, and alternative values areprovided in Table 7.11.
TABLE 7.11 (NEW)RELATIONSHIPS BETWEEN TROPHIC INDEX (TI), SURFACE CONCENTRATIONS OF CHLOROPHYLL-A (CHL-A), TOTALPHOSPHORUS (TP), TOTAL NITROGEN (TN), SECCHI DEPTH (SD), AND TROPHIC CLASS1 AND TROPHIC STATE
ADJUSTMENT FACTOR (αI)
TI

Chl-a
(µg/L)

TP(µg/L)

TN(µg/L)

SD(m)

Trophic Class

Trophic State Adjustment Factor

αiRange and (recommended value)<30 - 40

0 - 2.6

0 - 12–<350>4Oligotrophic

0.7 (0.7)

40 - 50

2.6 - 20

12 - 24–350-650

2-4

Mesotrophic

0.7 - 5.3 (3)50 - 70

20 - 56

24 - 96650-1200

0.5 - 2

Eutrophic

5.3 - 14.5 (10)70 - 100+

56 - >155

96 - >384

>1200

< 0.5

Hypereutrophic

14.5 - 39.4 (25)1(Carlson 1977), (Smith et al. 1999)

Tier 2
Under Tier 2, country-specific emission factors may be developed that take into account national circumstances
as well as specific properties of individual reservoirs including: reservoir operation, size, and depth; relative
locations of oxic/anoxic water and water intakes; trophic status; sedimentation and sequestration of carbon; andother environmental (e.g. seasonal ice cover) and management factors. CH4 emissions due to wastewater inflow

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may be estimated using the guidance in Volume 5, Chapter 6 and subtracted from reservoir emissions to avoid
double counting (see Box 7.2).
BOX 7.2 (NEW)ADDITIONAL INFORMATION ON EMISSIONS ARISING FROM WASTEWATER WITHIN RESERVOIRSEmissions of CH4 from both Land Converted to Flooded Land and Flooded Land Remaining
Flooded Land result from the degradation of autochthonous and allochthonous organic carbon inanoxic conditions (Bastviken et al. 2004). Allochthonous organic carbon from treated and/or
untreated wastewater may reach the flooded land area and be converted to CH4 (Deemer et al., 2016).
At Tier 2 and 3 it is a good practice to estimate CH4 emission from wastewater treatment anddischarge using the guidance in Volume 5, Chapter 6 and subtract them from reservoir emissions, toavoid double counting.

Tier 3
Under Tier 3, emission factors derived from models (mechanistic or statistical) or measurement campaigns may
be used instead of the default equations and/or default factors (see Annex 7.1). It is anticipated that a mix ofcountry-specific emission factors and modelled values will be used when the latter do not cover the full range ofenvironmental and management conditions within a country. The development of reservoir- or region-specificemission factors that are influenced by eutrophication is discussed below. CH4 emissions due to wastewater inflow
may be estimated using guidance provided in Chapter 6, Volume 5 of the 2006 IPCC Guidelines and subtracted
from the reservoir emissions to avoid double counting (see Box 7.2). The derivation of reservoir or region-specificfactors should be clearly documented.
Reservoirs or other constructed wetlands cause a perturbation of the natural processes of decay to the atmosphereof the organic matter contained in the water, so altering the natural pathway to GHG emissions of such organic
matter when stored in such flooded land. The perturbation effect can be considered the anthropogenic componentof the GHG emissions from the reservoirs. Approaches based on the mass balance of the organic carbon inputs
and its decay also qualify as Tier 3 methods to estimate the emissions from reservoirs or other constructedwaterbodies based on the Managed Land Proxy, caused by conveying freshwaters into reservoirs or otherconstructed wetlands.

Choice of Activity Data
Several different types of activity data may be needed to estimate Flooded Land emissions, depending on the Tierand the known sources of spatial and temporal variability within the national territory.

Tier 1Country-specific data on the area of reservoirs within each climate zone are required to estimate CH4 emissions
from flooded land. Estimates of flooded land area for reservoirs behind large dams can be obtained from theInternational Commission on Large Dams (ICOLD 1988), from the World Commission on Dams report (WCD
2000) , or from the Global Reservoir and Dam (GRanD) database (Lehner et al. 2011b). However, country-specificdatasets are likely to be more complete.

Tier 2 and 3
Estimates of flooded land area for reservoirs can be obtained from a drainage basin cover analysis or from anational dam database. Because flooded land area could change over time due to climate variation and change andmanagement activities, countries should use updated and recent data from national databases in order to obtain
more accurate emission estimates. Water withdrawal depths and anoxic zone depths are required for estimating
downstream emissions at the Tier 2 level. These data can be obtained from water utilities responsible for dam
operation and maintenance as well as from national dam operation databases. Tier 3 approaches can also include
more detailed activity data on, for example, effects of climate variability on water surface area and reservoir
management, but the exact requirements will depend upon the model or measurement design.
Data to directly calculate the trophic status adjustment, αi, (Eq 7.11, Table 7.11) can usually be sourced from water
quality databases held by the relevant water authorities. Remote sensing of Chl-a concentrations may also be
possible for larger reservoirs.

OTHER CONSTRUCTED WATERBODIES (FRESHWATER PONDS, SALINEPONDS, CANALS AND DITCHES)
The procedure presented here expands the methodology developed for quantifying CH4 emissions from drainage
ditches in organic soils described in the 2013 Wetlands Supplement, to include all other constructed waterbodies
apart from reservoirs, which are considered separately in the previous section. The approach described here allows

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Chapter 7: Wetlands

for the reporting of emissions from other Flooded Lands including constructed freshwater and saline ponds used
for agriculture, aquaculture or other activities (e.g. recreation), and canals and ditches. This includes ponds within
settlements; however, note that CH4 emissions associated with wastewater are considered elsewhere (Volume 5,
Chapter 6, 2019 Refinement). For Managed Land categories on organic soils inventory compilers may choose to‘embed’ emissions from small channels such as drainage ditches within their reporting of other Managed Landcategories (using Equation 2.4, Section 2.2.2.1 of Chapter 2, Drained Inland Organic Soils, of the 2013 Wetlands
Supplement 1). The same emissions should however not be included in Flooded Lands if they are included other
Managed Land categories.

Choice of Method
Methodology is provided for estimating CH4 emissions from all other constructed waterbodies, including ditches
and ponds. If CH4 emissions from other constructed waterbodies are a key category, then it is good practice forthe compiler to develop country-specific emission factors with application of a Tier 2 method or develop a country
specific method with a Tier 3 approach to reduce overall uncertainty, incorporating variations in inundation
regimes due to inter-annual and seasonal variation in water levels, management or other factors. All otherconstructed waterbodies are assumed to emit CH4 at a constant average rate for as long as the land remains flooded.
However, waterbodies may move between emission categories as a function of changes in site factors if higher
tier approaches are applied. Compilers could use different tiers for subcategories within the Other constructedwaterbodies category, depending on the importance of different waterbodies and the availability of activity data.
Guidance on the development of country-specific factors or methods is provided below in Tier 2 and Tier 3
approaches.

Tier 1The Tier 1 method extends the methodology developed for quantifying CH4 emissions from drainage ditches inorganic soils for the 2013 Wetlands Supplement (Section 2.2.2.1) to include a wider range of constructedwaterbodies. At Tier 1, emission factors are not stratified by climate zone or trophic status, but this can beincorporated at Tier 2 and 3. See Annex 7.1 for details of how default emissions factors were derived.
Total emissions are calculated for a given waterbody type using Equation 7.12.
EQUATION 7.12 (NEW)
ANNUAL CH4 EMISSION FROM OTHER CONSTRUCTED WATERBODIES
6

3 notherw , j

FCH 4other = ∑∑ ∑ ( Aj , w,i • EFCH 4, w • α j , w,i )w 1 =i 1=j 1 =

Where:

FCH 4 other= Total annual flux of CH4 from ponds and ditches [kg CH4 yr-1]

A j , w,i

= Area of other waterbody ‘i’ of type 'w' in climate zone 'j' [ha].

α j , w,i

= Emission factor adjustment for trophic state other waterbody 'i' of type 'w' located in climatezone 'j'. Currently = 1 for all tiers. [dimensionless] Refer to Eq. 7.11, Table 7.11.

EFCH 4, w= Emission factor for other waterbody of type 'w' [kg CH4 ha-1 y-1]. Refer to Table 7.15.

notherw, j= Number of other waterbodies of type 'w' in climate zone 'j'i= Summation index for the number of other waterbodies of type 'w' in climate zone 'j'j= Summation index for climate zones (j = 1-6, e.g. Table 7.12)

w= Summation index for waterbody classes (Table 7.12).

Tier 2The Tier 2 approach for CH4 emissions from constructed agriculture and aquaculture ponds, and from canals andditches, incorporates country-specific information in Equation 7.19 to estimate the emissions. Tier 2 emission
1

Note that the approach described to estimate ditch CH4 emissions in the 2013 Wetlands Supplement combined these emissions with thosefrom adjacent terrestrial areas, to provide a single emission estimate. Implicitly, this approach considered ditches to form part of the terrestrial
land-use category, rather than as a separate Flooded Land category. Either approach may be used, but not both.

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factors may be further stratified by sub-classifying waterbodies according to type (w) and trophic status (αj,w,i). In
addition, it may be possible to incorporate additional modifiers such as soil type (e.g. mineral versus organic);
water flow rate; inter-annual and seasonal variation in water levels; salinity; presence of emergent vegetation(which may increase emissions) and species (for aquaculture); or take account of site management activities that
may increase or decrease overall CH4 emissions (e.g., controlling organic matter loadings or aeration, including
pond drainage).

Tier 3
A Tier 3 approach for constructed ponds and ditches may specifically address the influence of different soils andland-uses within the catchment area of each waterbody as controls on organic matter and nutrient inputs. It could
also disaggregate the different components of CH4 emissions (diffusive flux across the water surface, ebullitionand plant-mediated emissions) and the associated controlling factors in order to provide more site-specificemission estimates. Compilers may also consider use of models that incorporate within-year and between-year
variation in emissions as a function of climatic or land-management variability, water level variability or
maintenance activities such as dredging and the duration of periodic drainage when sediments are exposed to air.
Tier 3 approaches are likely to require the development of a process-based model to address these additionalvariables and activities influencing emissions as the small size and large number of waterbodies in some countries
may make measurement-based approaches infeasible. For aquaculture ponds, Tier 3 approaches could also include
models incorporating management practices (e.g. species, yield, aeration, drainage regimes).

Choice of Emission Factors
Tier 1
Tier 1 emission factors for agriculture and aquaculture ponds, and from canals and ditches, are provided in Table
7.12. Emissions from ponds are separated into Freshwater Ponds with water column salinity < 18 ppt and Saline
Ponds with salinity of > 18 ppt, consistent with the 2013 Wetlands Supplement (Chapter 4, Annex 4A.1 salinitybased definitions). At present, available data are not sufficient to derive emission factors for any category by
climate zone, or to disaggregate emissions from canals, drainage channels and ditches, which are therefore
considered as a single Tier 1 category. Disaggregation by surrounding land-use, nutrient loading and/or yield isalso not currently possible at Tier 1. For ditches in organic soils, the Tier 1 emissions factors presented in Table
2.4 of the 2013 Wetlands Supplement may be used.
TABLE 7.12 (NEW)CH4 EMISSION FACTORS FOR OTHER CONSTRUCTED WATERBODIES (FRESHWATER PONDS, SALINE PONDS, CANALS,DRAINAGE CHANNELS AND DITCHES)
Waterbody typew

Climatezone

EFCH4 a(kg CH4

ha-1 yr-1)

95% confidence intervalsb(kg CH4

No. of sites

ha-1 yr-1)

Saline ponds

1

All

30

16-55

15

Freshwater andbrackish ponds

2

All

183

118-228

68

Canals and ditchesc

3

All

416

259-669

24d

Emissions factors for each category were calculated from the mean of log10-transformed values, because untransformed observations
showed a positively skewed distribution in all casesa95% confidence intervals shown are derived from standard errors, and thus represent the uncertainty in the mean emission factor rather
than the variability of the original measurements.
bc

For Emission Factor for ditches in organic soils refer to Table 2.4, 2013 Wetlands Supplement.

Ditch data are mostly aggregated to study level, where studies reported multiple measurements from the same ditch network or fromsites in close proximity; therefore the total number of individual ditches used to derive the emission factor exceeds the number shown.

dReferences. Saline ponds: (Cameron et al. 2016), (Castillo et al. 2017), (Chen et al. 2015), (Hai et al. 2013), (Strangmann et al. 2008),(Vasanth et al. 2016), (Yang et al. 2015). Freshwater and brackish ponds: (Baker-Blocker et al. 1977), (Casper et al. 2000), (Grinham2018), (Hu et al. 2016), (Huang 2016), (Liu et al. 2017), (Merbach et al. 1996), (Natchimuthu et al. 2014), (Selvam et al. 2014),(Stadmark & Leonardson 2005), (van Bergen 2015), (Singh et al. 2000), (Xiong et al. 2017), (Yang et al. 2017), (Zhu et al. 2016).
Canals and ditches: (Best & Jacobs 1997), (Chamberlain et al. 2015), (Chistotin 2006; Chistotin et al. 2006), (Evans et al. 2017),(Harrison 2003), (Hendriks et al. 2007), (Kosten et al. 2018), (McPhillips et al. 2016), (McNamara 2013), (Peacock et al. 2017), (SchrierUijl et al. 2010), (Schrier-Uijl et al. 2011), (Selvam et al. 2014), (Sirin et al. 2012), (Teh et al. 2011), (Van Den Pol-Van Dasselaar et al.
1999), (Vermaat et al. 2011), (Wang et al. 2009), (Yu et al. 2017).

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Chapter 7: Wetlands

Tier 2
At Tier 2, country-specific emission factors may be further stratified according to waterbody type, nutrient status,
water levels or other potential explanatory factors (e.g. management practices or yield for aquaculture), as
described in the preceding section.

Tier 3
To develop a model-based Tier 3 approach, additional empirical data are needed to define relationships between
each component of the CH4 emission and the relevant explanatory variables. These components could include theeffects of temperature, organic matter and nutrient supply and management processes such as periodic drainage;effects of salinity, water depth and flow on CH4 production in the sediment and oxidation within the water column;
relationships between sediment composition and bubble production; and influence of vegetation type and coveron plant-mediated emissions.

Choice of Activity Data
Activity data consist of the total area of (non-reservoir) constructed waterbodies, stratified according to thewaterbody type and any additional factors used to estimate emissions. Since flooded land area could change overtime, countries should consider this in developing their time series of activity data, attributing land cover to theappropriate category. Countries may use older data sources to establish time series data as well as updated andrecent data. Tier 2 and Tier 3 approaches are preferably based on national databases to track flooded land surface
area in order to obtain more accurate emission estimates. For aquaculture ponds, additional data on product yields
from ponds (FAO data) or management could be collected and related to CH4 emissions to derive more accurate
emission estimates.

Tier 1
Activity data required to support Tier 1 reporting are either complete mapping data for all constructed waterbodies,or alternatively a reliable estimate of the proportion of land area occupied by each waterbody type, such as
estimates derived from a land use survey. For agricultural ponds, it may be possible to evaluate small representative
areas within a larger land category in order to estimate the total proportion (and therefore total area) of ponds
present (Lowe et al. 2005). The Ramsar Convention (Ramsar 2005) provides guidance on mapping of wetlands(Annex III) which can be used to determine the area of Other constructed waterbodies. Additional guidance formapping agricultural ponds can be found in (Shaikh et al. 2011) and MDBC (2009) (Cunningham et al. 2009).
The minimum recommended scale of mapping is 1:5000 (50m x 50m or 0.25 ha), which could be used if
appropriate data are available, for example from Landsat remotely sensed imagery (Pekel et al. 2016). Other
satellite imagery has a higher resolution, for example Sentinel 2 data have a resolution of 10 m, sufficient to detectmany smaller ponds, and are freely available. In many cases, drainage occurs at regular spacing within agriculturallandscapes, such that the proportion of ditches in an area can be estimated from data on mean ditch width andspacing, as described in Section 2.2.2.1 of the 2013 Wetlands Supplement (the Fracditch calculation). For these areas,
inventory compilers may choose to report these emissions within the appropriate land category, or separately in
the Flooded Lands category. For irregularly distributed ditches or other constructed channels such as canals, it
may be possible to estimate overall extent and area by digitizing or estimating total channel length within
representative areas. For area of aquaculture ponds, estimates of area may be available from remote sensing
imagery (Ottinger et al. 2017) or national databases. If waterbodies vary substantially in their spatial extent
through the year, the annual average (rather than annual maximum) inundated area may provide the mostappropriate basis for flooded land area estimation.

Tier 2
Additional activity data required to apply a Tier 2 approach are likely to include information on waterbody
distribution (e.g. from remotely sensed imagery), waterbody type, nutrient status, flow rates, vegetation and otherfactors as described in the Choice of Method section. Additional management-related factors may be considered if
these affect emissions, for example if waterbodies are subject to large seasonal or short-term changes in waterlevel and area, this may produce different CH4 emissions that a waterbody with the same average surface area but
more constant water levels. For aquaculture ponds national databases of pond area or pond yields on an area basis,
disaggregated by region or species cultivated could be used to increase accuracy of CH4 emission estimates.

Tier 3Tier 3 approaches could include dynamic modelling of emissions evaluated from monitoring of greenhouse gas
concentrations and fluxes in representative systems or measurements of emissions on fine spatial and temporalscales. Additional activity data required to apply a Tier 3 approach are likely to include information on waterbody
distribution from remotely sensed imagery (which for drainage ditches could include high resolution aerial
photography), waterbody type, nutrient status, flow rates, vegetation and other factors as described above. National
level information capturing differing pond management (e.g. whether ponds are intensively managed or abandoned

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Volume 4: Agriculture, Forestry and Other Land Use(Gusmawati et al. 2016), particularly where pond management influences CH4 emissions (e.g. through drainage,(Yang et al. 2015)) may also be appropriate to incorporate within a Tier 3 method.

7.3.2

Land Converted to Flooded Land7.3.2.1

TOTAL CO 2 E MISSIONS FROM L AND C ONVERTED TO
F LOODED L AND

RESERVOIRSConversion of land to Flooded Land is a disturbance that affects all five terrestrial C pools in the area impounded(above-ground biomass, below-ground biomass, litter, dead wood and soil organic matter; see 2006 IPCC
Guidelines (Volume 4 Chapter 2, Fig. 2.1). The 2006 IPCC Guidelines and 2013 Wetlands Supplement, in addition
to Chapter 2 of this volume, give guidance on how to estimate the five carbon pools in the land to be flooded andguidance is provided in Chapter 12 for estimating harvested wood products (HWP). This Chapter gives guidanceon emissions related to land use conversion and the subsequent emissions.
Carbon stock changes in the five pools that occur prior to Land Converted to Flooded Land need to be estimatedusing the guidance in other chapters (See Volume 4, Chapter 2; Equation 2.3). The amount and fate of flooded
biomass depends largely on management decisions prior to flooding. The area to be impounded may be totally or
partially cleared of biomass including vegetation and the organic matter in soils prior to flooding. Anothermanagement procedure may be the burning of the biomass. If the pre-impoundment area was forested, and theforest was harvested before flooding, part of the biomass removed can go to HWP, but organic matter fromgrassland or cropland most likely remains.
The time elapsed since flooding has a significant influence on greenhouse gas fluxes from Flooded Lands and also
on the partitioning of the gases. Statistical analyses on reservoirs worldwide indicate that there is a rapid surge ofemissions immediately following flooding, after which emissions return to a relatively stable level. The rate of the
post-flooding decrease in emissions may depend on the region in which a reservoir is located and can differ
between CO2 and CH4, but seems to occur mainly during the initial decade following flooding.
Evidence suggests that CO2 emitted during approximately the first decade after flooding results from decay ofsome of the organic matter on the land prior to flooding. Upon flooding, the easily degradable carbon and nutrientsare made available to the microbial community and metabolized. Beyond this time period, CO2 emissions are
sustained by the input of organic material transferred into the flooded area from the watershed, (Houel 2003),(Hélie 2004), (Cole & Caraco 2001), and would have occurred in the absence of flooding, albeit displaced in space.
In addition to managed lands, unmanaged lands such as natural forests and peatlands, existing (smaller)
waterbodies and other land cover types not considered to be managed land may be converted to Flooded Land.
This guidance describes methods for reporting emissions from each land use / land cover type converted to Flooded
Land.

Choice of Method
Organic matter is subject to decay after flooding and the rate of decay diminishes over time following initialinundation. Therefore, it is not appropriate to report all C losses from biomass, dead wood, litter and soil organic
matter in the first year after land is converted to Flooded Land. Because Land Converted to Flooded Land isdefined as the first 20 years after flooding, the expected total CO2 emissions during the 100-year lifespan of thereservoir from the flooded stock of organic matter are allocated to these 20 years (see below and Annex 7.1 Fig
A4). C stocks are estimated using existing methodologies when possible (e.g., Volume 4, Chapter 2).
Organic C pools that remain in the impoundment area after flooding are subject to slow decomposition constrainedby reduced presence of oxygen. The fate of organic matter removed from the area prior to flooding can vary. For
example, biomass removed from the impoundment area prior to impoundment, e.g., by harvesting of timber, slashor stumps, is reported according to the guidance for CO2 emissions and removals (Volume 4, Chapter 2.3). The
CO2 and non-CO2 emissions of deliberately burned biomass are reported according to guidance in other chapters(See Volume 4, Chapter 2). The biomass remaining in the impoundment area after flooding becomes submerged(except for that in the drawdown zone) and a fraction of this organic matter is subsequently decomposed to CO2(for more details, see Annex 7.1).
Annex 7.1 explains how the G-res model estimates CO2 emissions for land converted to Flooded Land using
average organic carbon stock in the top 30 cm soil layer as an empirically-based approximation for the total flooded
organic matter decay (Annex 7.1, Section 1.5). Tier 1 emission factors are derived by determining the average,

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Chapter 7: Wetlands

spatially interpolated soil organic C stock for the flooded landscape area from a global soil carbon map (FAO, ordefault reference soil organic C stocks from Volume 4, Chapter 2. Table 2.3).

Tier 1
Emission factors for CO2 from the reservoir surface, EFCO2,j, in the six aggregated climate zones are provided inTable 7.13. The emission factors correspond to the total CO2 emission attributable to the reservoir and integrate
both spatial and temporal variations and have been derived from the application of empirical models to a large(>6000) number of reservoirs with a worldwide distribution (see Annex 7.1 for details and (Prairie et al. 2017a))
and are averaged per climate zone.
EQUATION 7.13 (NEW)
ANNUAL ON-SITE CO2-C EMISSIONS/REMOVALS FROM LAND CONVERTED TO FLOODED LAND
6 nres j

FCO2tot = ∑ ∑ Atotal , j , i • EFCO2 age ≤ 20, j=j 1 =i 1

Where:

FCO2tot= Total annual emission (removal) of CO2 from Land Converted to Flooded Land (Reservoirs≤ 20 years old), tonnes CO2-C yr-1.

Atotal , j , i= Total area of reservoir water surface for reservoir 'i' located in climate zone 'j', ha.

EFCO2 age ≤ 20, j= Emission factor for CO2 for reservoir ≤ 20 years old in climate zone 'j', tonnes CO2-C ha-1y-1. Refer to Table 7.13.

nres j= Number of reservoirs ≤ 20 years old in climate zone 'j'i= Summation index for the number of waterbodies of same type in same climate zonej

= Summation index for climate zones (j = 1-6, see Table 7.13)

Tier 2The methodology for estimating Tier 2 annual carbon loss as CO2 on recently flooded land (<20 years old) uses
Equation 7.13 substituting in the emission factor calculated using Equation 7.14. Tier 2 methods for determining
annual CO2 emissions from land converted to Flooded Land use knowledge about climate zone and distribution ofsoil organic carbon stock of the land prior to flooding in order to develop country-specific factors.
EQUATION 7.14 (NEW)
ANNUAL CO2-C EMISSIONS/REMOVALS FROM LAND CONVERTED TO FLOODED LAND INCLUDING
SOIL CARBON STOCKS
nsoil

EFCO2 j ,i = ∑φi ,k • SOC j ,k • M j
k =1

Where:

EFCO2 j ,i

= Emission factor for CO2 for reservoir 'i' climate zone 'j', tonnes CO2-C ha-1 y-1.

SOC j , k

= Soil C stock (tonnes C ha-1 in 0-30 cm depth) values per climate zone 'j' and mineral soil
type (k) from Table 2.3 (Volume 4, Chapter 2), for undrained and drained peatlands using
Table 2.6 (2013 Wetlands Supplement) with conversion from dry organic matter to organiccarbon (see A7.1.2.2), or from FAO Global Soil organic C map (http://www.fao.org/globalsoil-partnership/resources/highlights/detail/en/c/1070492/), or country specific SOC stocks.

i= Summation index for the number of waterbodies of same type in same climate zonej

= Summation index for climate zones (j = 1-6, see Table 7.13)

k= Summation index for soil typeφi , k= The fraction of reservoir 'i' area with soil type k, dimensionless2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories

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Mj

between emissions estimated from G-res (integrated 100 year emissions post-flooding
reported as a constant yearly flux for the first 20-year post-flooding) and soil C stocks andclimate. (see Annex 7 for more explanations), y-1. Values in Table 7.14.
= Number of soil types (= 6, see Volume 2, Table 2.3)

nsoil
nsoil

Note that ∑φi , k ≤ 1 will be nearly 1 if only a river existed prior to inundation of a large reservoir. In contrast,
k =1

the value will be close to 0 if the reservoir is a small expansion of a natural lake.
Tier 2 may include: 1) a derivation of country-specific emission factors; 2) specification of climate sub-zones
considered suitable for refinement of emission factors; 3) a finer, more detailed classification of management
systems with a differentiation of pre-flooding land-uses; 4) differentiation of emission factors by time since
flooding, and 5) a finer, more detailed classification of nutrient status or other water quality attributes, e.g. nitrogen,phosphorus, and chlorophyll.
For compatibility of approach, country-specific Tier 2 factors for CO2 emissions and removals that are compiledusing domestic flux data measured at the water-atmosphere boundary should follow a similar general concept to
the G-res model, which is used in this guidance for generating Tier 1 emission factors (see details in Annex 7.1).
An alternative method can use observed data on the decay curve of CO2 release to the atmosphere from the surfaceof the waterbody. These observations include a declining annual CO2 emission due to the newly flooded organic
matter, and a natural annual background release of CO2 that is associated with catchment inputs and should not be
included in the annual emissions. Instead, the natural emissions should be subtracted from the declining emissions
in order to obtain the apparent CO2 release from the land converted to Flooded Land. The shape of the declining
curve of annual CO2 release does not need to follow a specific equation, as long as it asymptotically declines as
reservoirs age and can be integrated.
It is good practice to derive country-specific emission factors if measurements representing the national
circumstances are available. Countries need to document that methodologies and measurement techniques are
consistent with the scientific background for Tier 1 emission factors in Annex 7.1. Moreover, it is good practicefor countries to use a finer classification for climate and management systems. Note that any country-specificemission factor must be accompanied by sufficient national or regional land-use/management activity andenvironmental data to represent the appropriate climate sub-domains and management systems for the spatial
domain for which the country-specific emission factor is applied.

Tier 3CO2 emissions/removals at Tier 3, compared to those at Tier 2, would use detailed data and models of soil carbon
and other remaining carbon pools prior to flooding and time series of CO2 emissions after flooding for a range ofreservoirs that encompass an appropriate range of environmental conditions. Details for the development of
measurement and model-based methods are discussed in Annex 7.1.

Choice of Emission Factor
Tier 1CO2 emissions are calculated using the emission factors in Table 7.13.

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Chapter 7: Wetlands

TABLE 7.13 (NEW)
CO2-C EMISSION FACTORS FOR RESERVOIRS ≤ 20 YEARS OLD – LAND CONVERTED TO FLOODED LAND
CO2-C Emission Factors EFCO2 age<20,j(tonnes CO2-C ha-1 y-1)

Climate Zonej

Average

Lower and upper 95% CI of mean

Boreal1

0.940.84 –1.05

Cool Temperate

2

1.02

1.00–1.04

Warm temperate dry

3

1.70

1.66 –1.75

Warm Temperate moist

4

1.46

1.44–1.48

Tropical dry/montane

5

2.95

2.86–3.04

Tropical moist/wet

6

2.77

2.71–2.84

The emission factors are derived from model outputs for each climate zone (Annex A7.1.2.1). The aggregation into 6 climate zones is
described in Annex section A7.1.2.1.

Tier 2 and 3
The Tier 2 approach for estimating total CO2 emissions from Flooded Land incorporates country-specificinformation with derivation of country-specific scaling factors. The compiler may address other drivers ofemissions including: 1) specification of climate sub-zones considered suitable for refinement of emission factors;
2) a finer, more detailed classification of management systems including estimation of emissions associated withdrawdown zones during the time period of low water level in reservoirs; 3) time-series data that incorporateseasonal/annual variation in CO2 emissions. Country-specific soil maps, measured in situ data, or updated versionsof global soil databases that can be used in estimating the soil organic carbon stocks for 0-30 cm top soil layer
within the flooded area using GIS tools. Table 7.14 provides scaling factor values that may be used with the Tier
2 method.

Choice of Activity Data
Tier 1
Areas of newly flooded lands are available from dam operators such as hydropower companies or responsible
government agencies. In many cases recent impoundments have been extensively described in Environmental
Impact Assessment (EIA) documents of specific projects. Those documents are often publicly available. In absenceof such information sources, satellite images and aerial images taken during the past 20 years are commonly
available and allow determination of flooded land areas by comparison of pre-impoundment and postimpoundment images.

Tiers 2 and 3
Detailed area information is needed for Tier 2 and 3 approaches, and can be found in geographic information
products, reservoir statistics, or remote sensing products. Management systems for pre-impoundment land use
characteristics of the flooded land may be derived from project-specific EIA documents, forest surveys from thepre-impoundment period, or remotely-sensed land cover assessments.
Countries could consider differentiating the fluxes from the drawdown zone. Estimation of drawdown zone areas
can be done using remote sensing images taken during the time period of low water level in reservoirs or fromreservoir managers.
Many countries also monitor water quality parameters from watercourses impacted by management activities.
These include industrial effluent disposal, mining, land drainage, and wastewater treatment. In the best cases, timeseries of water quality parameters are available in national registers for over 20 years and may be useful for
applying Tier 3 emission factors differentiated by those parameters.

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TABLE 7.14 (NEW)SCALING FACTOR VALUE M [Y-1] FOR EQUATION 7.14, ANNUAL ON-SITE CO2-C EMISSIONS/REMOVALS FROM LANDCONVERTED TO FLOODED LAND.
M

Aggregated climate zone
IPCC climate zones

j

Average

Lower and upper
95% CI

Number ofreservoirs

Boreal10.00910.0075-0.0107

118

Cool temperate

20.01460.0141-0.0151

2103

Warm temperate dry

Warm temperate dry

30.05680.0541-0.0595

679

Warm temperate moist

Warm temperate moist

40.03020.0291-0.0312

2095

Tropical dry/montane

50.09000.0846-0.0954

902

Tropical moist/wet

60.06680.0628-0.0708

920

Boreal dry
Boreal moist
Polar dryPolar moist
Cool temperate dry
Cool temperate moist

Tropical dry
Tropical montane
Tropical moist

Note: Scaling factors were derived from the integrated CO2 emissions attributable to the reservoir estimated from the G-res model(see Annex 7.1 for details, (Prairie et al. 2017b) expressed as a fraction of soil organic carbon content (SOC) and applied to the first
20 years post-impoundment. The aggregation into 6 climate zones is described in Annex 1, section A7.1.2.1.

OTHER CONSTRUCTED WATERBODIES (DITCHES, CANALS, FARMPONDS AND AQUACULTURE PONDS)No specific methodologies are provided to estimate CO2 emissions resulting from land conversion to otherconstructed waterbodies as there are insufficient CO2 emission data. However, compilers may estimate CO2
emissions for coastal wetlands converted to aquaculture ponds by excavation based on guidance in the 2013
Wetlands Supplement (Chapter 4, Coastal Wetlands). For all types of pond created by damming, the methodology
described above to estimate CO2 emissions from land converted to reservoirs may be used.

7.3.2.2 T OTAL N ON -CO 2 E MISSIONS FROM L AND C ONVERTED TO
F LOODED L AND
RESERVOIRSIn reservoirs, high levels of CH4 emissions can occur in the first 20 years following flooding (see Annex 7.1). No
guidance on estimating N2O emissions from flooded land is provided here because N2O emissions from aquatic
systems are indirect N2O emissions from managed land that are addressed in other sections of this guidance (e.g.
Volume 4, Chapter 11).

Choice of Method
Tier 1
For Tier 1, guidance can be found in section 7.3.1 Non-CO2 emissions from Flooded Land Remaining Flooded
Land. The Tier 1 approach to calculate CH4 emissions from Land Converted to Flooded Land (flooded ≤ 20 years
prior to reporting year) is based on Equation 7.15, which differs from Equation 7.10 only in the values of theemission factors, EFCH4 age<20,j.

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Chapter 7: Wetlands

EQUATION 7.15 (NEW)
ANNUAL CH4 EMISSIONS FOR RESERVOIRS ≤ 20 YEARS OLD FOR LAND CONVERTED TO FLOODEDLAND

FCH 4tot = FCH 4 res + FCH 4 downstream
6 nres j

FCH 4 res = ∑ ∑ αi (EFCH 4 age≤ 20, j • Atot j,i )

(A)
(B)

=j 1 =i 1

6 nres j

FCH 4 downstream = ∑ ∑ αi (EFCH 4 age≤ 20, j • Atot j,i )• Rd, i(C)=j 1 =i 1

Where:

FCH 4tot= Total annual emission (removal) of CH4 from all reservoirs ≤ 20 years old, kg CH4 yr-1

FCH 4 res= Annual reservoir surface emissions of CH4 from all reservoirs ≤ 20 years old, kg CH4 yr-1

FCH 4 downstream= Annual emissions of CH4 originating from the reservoir but emitted downstream of dam.
For Tier 1, equation 7.15 (C) simplifies to FCH 4 downstream = FCH 4 res • Rd , kg CH4 yr-1

Atot j,i= Total area of reservoir water surface for reservoir ≤ 20 years old 'i' located in climate zone
'j', ha

EFCH 4 age≤ 20, j = Emission factor for CH4 emitted from the reservoir surface for reservoir ≤ 20 years old
located in climate zone ‘j’, kg CH4 ha-1 y-1 (Refer Table 7.15)

Rd= A constant equal to the ratio of total downstream emission of CH4 to the total flux of CH4
from the reservoir surface, dimensionless. Equals 0.09 by default for Tier 1 (Table 7.10) andzero for all other reservoirs. See text below for Tiers 2 & 3 Rd values.

αi= Emission factor adjustment for trophic state in reservoir 'i' within a given climate zone,
dimensionless. Equals 1.0 by default for Tier 1. See Equation 7.11 for Tiers 2 & 3.

I

= Summation index for the number of reservoirs of ≤ 20 years in climate zone 'j'j= Summation index for climate zones (j = 1-6, see table 7.15)

nres j= Number of reservoirs ≤ 20 years old in climate zone 'j'

Tiers 2 and 3
For Tiers 2 and 3, refer to guidance in section 7.3.1, Non-CO2 emissions from Flooded Land Remaining Flooded
Land.

Choice of Emission Factor
Tier 1
Emission factors for CH4 via diffusion and ebullition for Land Converted to Flooded Land in the six aggregatedclimate zones are provided in Table 7.15. As for Flooded Land remaining Flooded Land (Table 7.9), the emission
factors integrate both spatial and temporal variations and have been derived from the application of empiricalmodels to a large (>6000) number of reservoirs with a worldwide distribution (see Annex 7.1 for details) and areaveraged per climate zone.

Tiers 2 and 3
For Tiers 2 and 3, refer to guidance in section 7.3.1, Non-CO2 emissions from Flooded Land Remaining Flooded
Land.

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TABLE 7.15 (NEW)CH4 EMISSION FACTORS FOR RESERVOIRS ≤ 20 YEARS OLD – LAND CONVERTED TO FLOODED LAND
Aggregated Climate Zone

CH4 Emission Factors EFCH4 age<20,j(kg CH4 ha-1 year-1)
jAverage

Lower and upper
95% CI of the mean

N

Boreal1

27.7

20.8–34.7

96

Cool Temperate

2

84.7

78.8-90.6

1879

Warm temperate dry

3

195.6

176.9-214.7

578

Warm Temperate moist

4

127.5

121.5-133.4

1946

Tropical dry/montane

5

392.3

366.5-417.7

710

Tropical moist/wet

6

251.6

236.6-266.7

805

Note: The Emission Factors are derived from model outputs from N reservoirs in each climate zone. The aggregation into 6 climate zones
is described in Annex 1, section A7.1.2.1.

Choice of Activity Data
Tier 1
For Tier 1, refer to guidance refer in section 7.3.1, Non-CO2 emissions from Flooded Land Remaining Flooded
Land.

Tiers 2 and 3
For Tiers 2 and 3, refer to guidance in section 7.3.1, Non-CO2 emissions from Flooded Land Remaining Flooded
Land.

OTHER CONSTRUCTED WATERBODIES (DITCHES, CANALS, FARMPONDS AND AQUACULTURE PONDS)
Refer to guidance in section 7.3.1, Non-CO2 emissions from Flooded Land Remaining Flooded Land. There isinsufficient information to derive separate emission factors for CH4 emissions for recently constructed ponds,
canals and ditches.

7.3.3

Approach to provide indicative estimates of theanthropogenic component of total CO2 and non-CO 2
emissions (optional)

A method for estimating the contribution of human activities to total emissions from Flooded Land is provided
that uses the area of Managed Land and Unmanaged non-Wetland categories converted to Flooded Land to develop
indicative estimates of the anthropogenic component of total CO2 and non-CO2 greenhouse gas emissions. Thismethod includes the area that was not previously (before flooding) unmanaged lakes, rivers/streams andunmanaged wetlands, on the basis that emissions from these unmanaged lands are not reported in national
greenhouse gas inventories. For unmanaged lakes and rivers, which have similar CH4 emissions to reservoirs, thismethod is robust. When unmanaged wetlands are flooded this method could under- or over-estimate anthropogenic
CH4 and CO2 emissions because flooding may alter the greenhouse gas emissions and removals from theseunmanaged lands due to changes in biogeochemical processes (see Annex 7.1.1). However, there are insufficient
empirical data to provide guidance to estimate the changes in emissions from land that was unmanaged wetlands
after it is flooded. Additionally, CH4 emission factors from unmanaged wetlands, reservoirs and other constructedwaterbodies in many climate zones are broadly similar and thus when unmanaged wetlands are a small componentof the land surface before the area was converted to Flooded Land this method is robust. If unmanaged wetlands
occupy a high proportion of the surface of the land prior to flooding then countries may choose to better understandanthropogenic emissions at Tier 2 or 3 using methods described in section 7.3.1 and 7.3.2. However, previously
flooded lands where changes in hydrology lead to substantial changes in the characteristics and ecological functionof the area, or emissions and removals per unit area, may not be excluded from the calculation of indicative
estimates of the anthropogenic component of total greenhouse gas emissions.

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Chapter 7: Wetlands

An analogous approach to develop indicative estimates of the anthropogenic component of total greenhouse gas
emissions, following the same principles, could also be applied to other constructed waterbodies. Developing theseestimates will require a Tier 2 or 3 method.

INDICATIVE ESTIMATES OF THE ANTHROPOGENIC COMPONENT OFTOTAL CH 4 EMISSIONS IN FLOODED LAND REMAINING FLOODED LAND
Indicative estimates of the anthropogenic component of total CH4 emissions for Flooded Land Remaining Flooded
Land are estimated with the following equation (flooded > 20 years prior to reporting year) by using the area offlooded land that was not an unmanaged waterbody prior to flooding:
EQUATION 7.16 (NEW)INDICATIVE ESTIMATE OF THE ANTHROPOGENIC COMPONENT OF TOTAL ANNUAL CH4
EMISSIONS IN FLOODED LAND REMAINING FLOODED LAND=FCH 4 anthrop

6 nres j∑ ∑ α ( EF

=j 1 =i 1

i

CH 4 age > 20, j)• Aanthrop , j ,i + FCH 4 downstream

Where:

FCH 4 anthrop= Indicative estimate of the anthropogenic component of total annual emissions of CH4 fromflooded land, kg CH4 yr-1

Aanthrop , j ,i

= Area associated with the anthropogenic component of emissions and comprises all areas ofreservoir water surface for reservoir > 20 years old 'i' located in climate zone 'j', but excluding
areas that were unmanaged waterbodies (lakes and rivers), ha

FCH 4 downstream= Annual downstream CH4 emissions, estimated above (Equation 7.15), kg CH4 yr-1

αi

= Emission factor adjustment for trophic state in reservoir 'i' within a given climate zone.
[dimensionless] Equals 1.0 by default for Tier 1. See Equation 7.11 for Tiers 2 & 3.

EFCH 4 age > 20, j = Emission factor for CH4 emitted from the reservoir surface for reservoir > 20 years old
located in climate zone 'j', kg CH4 ha-1 yr-1 (Table 7.9).
In general, other Unmanaged Lands, including forest land and grassland, are not considered a significant sourceof CH4 emissions, and removals of CH4 are not recognized as an anthropogenic source category in the AFOLU
sector guidance. However some removal of CH4 can occur through oxidation of atmospheric CH4 bymethanotrophic microorganisms in aerated soils, but this flux is typically small when expressed per unit land area
(Oertel et al. 2016). Regardless, no guidance is provided to estimate CH4 removal from unmanaged forest land
and grassland.

INDICATIVE ESTIMATES OF THE ANTHROPOGENIC COMPONENT OFTOTAL CO 2 EMISSIONS IN LAND CONVERTED TO FLOODED LAND
Indicative estimates of the anthropogenic component of total CO2 emissions in Land Converted to Flooded Land(i.e. Reservoirs ≤ 20 years old) are calculated following the method described in section 7.3.1.1 but using Eq. 7.17
to calculate.
EQUATION 7.17 (NEW)INDICATIVE ESTIMATE OF THE ANTHROPOGENIC COMPONENT OF TOTAL ANNUAL CO2
EMISSIONS IN LAND CONVERTED TO FLOODED LAND
6 nres j(

FCO2 anthrop = ∑ ∑ EFCO2 age≤ 20, j • Aanthrop , j ,i
=j 1 =i 1

)

Where

FCO2 anthrop= Indicative estimate of the anthropogenic component of total annual emission of CO2 fromLand Converted to Flooded Land (reservoirs ≤ 20 years old), tonnes CO2-C yr-1.

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Aanthrop , j ,i

= Area associated with the anthropogenic component of emissions and comprises all areas ofreservoir water surface for reservoir ≤ 20 years old 'i' located in climate zone 'j', but excluding
areas that were unmanaged waterbodies (lakes and rivers) or unmanaged wetlands prior toflooding [ha]. Note: previously flooded lands where changes in hydrology lead to substantialchanges in the characteristics and ecological function of the area, or emissions and removals
per unit area, may not be excluded from the calculation of indicative estimates of theanthropogenic component of total greenhouse gas emissions.

EFCO2 age ≤ 20, j= Emission factor for CO2 for reservoir ≤ 20 years old in climate zone 'j', tonnes CO2-C ha-1y-1. Refer to Table 7.13.

INDICATIVE ESTIMATES OF THE ANTHROPOGENIC COMPONENT OFTOTAL CH 4 EMISSIONS IN LAND CONVERTED TO FLOODED LAND
Indicative estimates of the anthropogenic component of total CH4 emissions for Land Converted to Flooded Landcan be derived with the following equation (flooded ≤ 20 years prior to reporting year) by using the area of flooded
land that was not an unmanaged waterbody or unmanaged wetlands prior to flooding:
EQUATION 7.18 (NEW)INDICATIVE ESTIMATES OF THE ANTHROPOGENIC COMPONENT OF TOTAL ANNUAL CH4
EMISSIONS IN LAND CONVERTED TO FLOODED LAND=FCH 4 anthrop

6 nres j∑ ∑ α ( EF

=j 1 =i 1

i

CH 4 age ≤ 20, j)• Aanthrop , j ,i + FCH 4 downstream

Where:

FCH 4 anthrop= Indicative estimate of the anthropogenic component of total annual emissions of CH4 fromflooded land, kg CH4 yr-1

Aanthrop , j ,i

= Area associated with the anthropogenic component of emissions and comprises all areas ofreservoir water surface for reservoir ≤ 20 years old 'i' located in climate zone 'j', but excluding
areas that were unmanaged waterbodies (lakes and rivers) or unmanaged wetlands prior toflooding, ha. Note: previously flooded lands where changes in hydrology lead to substantialchanges in the characteristics and ecological function of the area, or emissions and removals
per unit area, may not be excluded from the calculation of indicative estimates of theanthropogenic component of total greenhouse gas emissions.

FCH 4 downstream= Annual downstream CH4 emissions, estimated above (Equation 7.15(C), kg CH4 yr-1

αi

= Emission factor adjustment for trophic state in reservoir 'i' within a given climate zone,
dimensionless. Equals 1.0 by default for Tier 1. See Equation 7.11 for Tiers 2 & 3.

EFCH 4 age ≤ 20, j = Emission factor for CH4 for Land Converted to Flooded Land, kg CH4 ha-1 y-1. Refer toTable 7.15.
i= Summation index for all reservoirs of age ≤ 20 years in climate zone 'j'j= Summation index for climate zones (j = 1-6, e.g. Table 7.15)

Choice of Activity Data
Activity data needed include area of Unmanaged Wetlands (Note: previously flooded lands where changes inhydrology lead to substantial changes in the characteristics and ecological function of the area, or emissions andremovals per unit area, may not be excluded from the calculation of indicative anthropogenic emissions) andnatural lakes that become a managed flooded land, and the final flooded land area in each climate zone. Activity
data required to support Tier 1 calculations are complete mapping for pre-flooding wetland and lake area estimatedfrom a land use survey, remotely sensed imagery (e.g. Landsat data) or other national maps and data bases.

7.3.4

7.28

Uncertainty Assessment

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Chapter 7: Wetlands

The two largest sources of uncertainty in the estimation of CH4 emissions from Flooded Land are the quality ofemission factors and estimates of the flooded land areas.

Flooded Land surface area
For reservoirs, national statistical information on the flooded area behind large dams (> 100 km2) should beavailable and will probably be accurate to within 10 percent. Where national databases on dams are not available,
and other information is used, the Flooded Land areas retained behind dams will probably have an uncertainty ofmore than 50 percent, especially for countries with large Flooded Land areas. Detailed information on the location,
type and function of smaller dams may be difficult to obtain, though statistical inference may be possible basedon the size distribution of reservoirs for which data are available. Reservoirs are created for a variety of reasons,and this will influence the availability of data. Consequently, uncertainty regarding surface area is dependent on
country specific conditions.
Uncertainties in estimating emissions and removals from other constructed waterbodies (ditches, canals, farm
ponds and aquaculture ponds) are to a large extent derived from assumptions and uncertainties in the area to which
the EFs are applied. Variation in salinity of aquaculture ponds may also contribute to uncertainty in CH4 emissions.

Emission factors
As shown in Tables 7.9 and 7.15, average emissions can vary both within and among climate regions. Therefore,
the use of any default emission factor will result in high uncertainty as reflected in the 95% confidence intervals
as discussed in Annex 7.1.
Downstream CH4 emissions occur primarily when anoxic and methane-rich hypolimnetic water (i.e. the lower
water layer in a stratified water column) is withdrawn from a reservoir and passed through the dam structure,including turbines in hydropower reservoirs, and discharged to a downstream river (see Annex 7.1 for a moredetailed description). Accordingly, downstream emissions are typically negligible in well-oxygenated reservoirs(Diem et al. 2012) or those with epilimnetic withdrawal (Beaulieu et al. 2014b), but can exceed emissions fromthe reservoir surface in thermally stratified systems with hypolimnetic withdrawal (Kemenes et al. 2007), (Abrilet al. 2005). At the Tier 1 level, downstream emissions are estimated from Rd, defined as the average ratio ofdownstream to surface emissions. Sources of uncertainty in Rd include differences among studies in how fluxes
from the reservoir surface and downstream or the reservoir were measured. Uncertainty can be reduced at the Tier
2 and 3 levels by accounting for the reservoir mixing patterns and withdrawal depths on a case-by-case basis.
To reduce the uncertainties on emissions factors, countries should develop appropriate, statistically-valid samplingstrategies that take into account natural variability of the ecosystem under study. When applicable, the distinction
between ice-free and ice-covered periods may be a significant improvement in accuracy (Duchemin et al. 2006).
Those sampling strategies should include enough sampling stations per reservoir, enough reservoirs and sampling
periods. The number of sampling stations should be determined using a recognized statistical approach (see(Goldenfum 2010) (UNESCO/IHA for measurement guidelines).
The EF values in Table 7.9 represent global averages and have large uncertainties due to variability in climate andmanagement practices, including depth of the waterbody, salinity of water, presence of emergent vegetation,
recharge rate and (for aquaculture) the intensity of management, including fish feeding characteristics and pond
aeration.
Uncertainties associated with the indicative estimates of anthropogenic component of total emissions
The methods to produce the indicative estimates of the anthropogenic component of total emissions from managed
flooded lands have additional uncertainties beyond the estimation of total emissions. The key uncertainty isdetermining the excluded areas that were unmanaged waterbodies (lakes and rivers) or unmanaged wetlands prior
to flooding. The unmanaged river and possibly lake area is particularly challenging to estimate if there is large
intra- or inter-annual variability in river water level, resulting in a highly variable river area over time. To address
this uncertainty, compilers may use the long-term mean river and lake area, but it should be highlighted that there
is a risk for higher uncertainty where the average area is challenging to assess.

7.4

COMPLETENESS, TIMES SERIESCONSISTENCY, AND QA/QC

No refinement.

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Annex 7A.1

Estimation of Default Emission Factor(s) for
greenhouse gas emissions from Flooded Lands

7A.1.1 Background on CH4 cycling in Flooded Land
CH4 emissions from aquatic environments are the combined result of CH4 production, oxidation and transport
processes, which are described in e.g. (Bastviken 2009), (Bridgham et al. 2013), (Duc et al. 2010), and (Bogard
et al. 2014) (the two former being reviews and the two latter describing updates). A summary is provided below:

Production and oxidation of CH 4
Methane production is a microbially-mediated process that primarily occurs in anoxic sediment. Sedimentmethanogenesis represents the terminal step in the anaerobic degradation of organic matter, and is strongly
stimulated by temperature, anoxic conditions, and high sedimentation rates. The last of these, sedimentation,
provides organic matter and promotes anoxia. Inhibition is induced by the presence of molecular oxygen (O2) andother alternative electron acceptors in organic matter degradation, such as nitrate, iron (III), manganese (IV) andsulphate. Because sulphate is common in waters with high salinity, methanogenesis in the upper sediments is often
low under saline conditions (Reeburgh 2007).

Methane oxidation in aquatic environments is primarily a microbial process in which dissolved CH4 is used as acarbon and energy source. Therefore, CH4 oxidation takes place at redox gradients where both CH4 and suitableelectron accepting compounds are present. Anaerobic CH4 oxidation using e.g. nitrate and sulphate has been
observed and sulphate-dependent CH4 oxidation can be important in saline sediments. In freshwater environments,
O2 dependent CH4 oxidation is considered to dominate (Bogard et al. 2014). By being confined to redox gradients,
CH4 oxidation is therefore often most intense in spatially restricted zones near the interface between anoxic andoxic conditions in water columns, or in the top millimetres of sediments overlain with oxic water (below a few
mm depth most sediments are anoxic). The oxidation of CH4 can be extensive and reported removal of dissolved
CH4 during passage through a zone with oxidation often range from 50 to >95% (Bastviken 2009). Aerobic CH4oxidation in situ is considered to be primarily substrate dependent, i.e. to depend largely on concentrations andsupply rates of CH4 and O2.

The transport of CH 4 through waterbodies
With reference to processes numbered in Figure 7A1, the transport of CH4 through a reservoir can be describedas follows (Bastviken 2009):
CH4 produced in anoxic sediments, and subsequently dissolved in the water, is transported along the concentration
gradient by Fickian transport (molecular diffusion or eddy diffusion) and, at times advection, into the hypolimnion
water (1). The transport of CH4 from the hypolimnion into the epilimnion is often very small due to limited mixing
between water layers and because extensive microbial CH4 oxidation occurs at the interface where both CH4 andO2 are present (Bastviken et al. 2008) (2). The release of CH4 from epilimnetic sediments is also constrained by
CH4 oxidation, similarly occurring at the oxycline in the top several mm of the sediment (3). However, water
movements such as waves can speed up CH4 transport across the epilimnetic sediment-water interface (Bussmann2005), reducing the fraction being oxidized. Additional epilimnetic CH4 can be sustained by production in oxic
water (Bogard et al. 2014) (4). The dissolved CH4 in surface water is emitted across the diffusive boundary layer
at the water-atmosphere interface (diffusive emission). The diffusive emission rates are stimulated by high CH4
concentrations and high turbulence in the water (5). The solubility of CH4 in water is rather low, and therefore
CH4 bubbles are formed in the sediment. Emissions to the atmosphere by ebullition occur when such CH4-richbubbles are released and rapidly rise through the water column into the atmosphere (6). Ebullition can be thedominant flux pathway, and is influenced by CH4 production rates in the sediment, physical triggers releasing
bubbles such as drops in barometric pressure, changes in the water level or waves. CH4 emissions can also occur
via rooted emergent aquatic plants with gas transporting aerenchyma tissue. These structures can function as gas
conduits between sediments and the atmosphere. Such plant-mediated emission can be substantial and depends on
CH4 production, plant abundance, activity and species composition. In reservoirs, water, with its dissolved CH4,
is withdrawn into the dam structure (D) inlet and released to the outlet river (7a and 7b). The dissolved CH4 canthen be degassed to the atmosphere upon passage through dam structures or emitted after release to the outlet river(8). Both degassing and reservoir-related emissions from the outlet river are a result of the reservoir, but occur
downstream of the reservoir surface and are collectively referred to in this chapter as downstream emissions.
Downstream emissions are low if oxic epilimnetic water with low CH4 concentrations is withdrawn (7a), but canbe high if anoxic, CH4 rich hypolimnetic water is withdrawn (7b).
The degassing of the water in the turbines is relevant in hydroelectric reservoirs only, but the other parts of thedescription in Figure A1 are valid for non-hydroelectric reservoirs and for non-reservoir waterbodies.

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Chapter 7: Wetlands

Figure 7A.1 (New)Methane related transport within and from waterbodies, exemplified
with a reservoir with an anoxic hypolimnion.

For explanations of numbered processes, see text.

Emissions of CH 4
Aquatic CH4 emissions are favoured by high CH4 production and by conditions facilitating transport pathways
where most CH4 escapes oxidation. Conditions leading to high whole-system CH4 production rates include low
salinity (Camacho et al. 2017), high temperatures (Yvon-Durocher et al. 2014), (Deemer et al. 2016), (DelSontro
et al. 2016), and a high load of labile organic matter (DelSontro et al. 2016), (DelSontro et al. 2018), (Deemer et
al. 2016). The overall CH4 production potential in freshwaters in a given climate zone is also positively related to
the flooded area. In this guidance: estimation of emissions from coastal aquaculture ponds (Tier 1) is improved byconsideration of salinity of the water as sulphides in seawater supress methanogenesis (Poffenbarger et al. 2011);
temperature is considered by separating emission factors by climate zone and including temperature seasonality
when generating emission factors (Tier 1); methanogenic habitat extent is considered by including the area of theflooded land in calculations (Tier 1); and the supply of labile organic matter is considered via a trophic stateadjustment option (Tier 2; see also below).
Conditions favouring rapid transport from sediments to the atmosphere by ebullition or via plants, bypassing CH4oxidation zones, include shallow water depth and a high abundance of emergent aquatic plants. These conditions
are indirectly considered at the whole climate zone level at the Tier 1 via validation to available data, but are highlyvariable among waterbodies and consideration for individual waterbodies can therefore only be performed at theTier 3 level. Downstream emissions also represent situations where high water turbulence causes rapid emissionof CH4 with little time for oxidation. Downstream emissions are considered at Tier 1, and are estimated using
empirical relationships between CH4 fluxes from waterbody surfaces and observed downstream emissions.

Trophic status and greenhouse gas emissions from Flooded Lands
Flooded lands with high inputs of nutrients and high rates of biological production (eutrophic systems) generally
emit CH4 to the atmosphere more rapidly on a per-area basis than less productive (meso- or oligotrophic) systems.
This relationship is seen in meta-analyses examining fluxes from many reservoirs (Narvenkar et al. 2013), (Deemer
et al. 2016), and a positive relationship between local primary production and CH4 emission has also been
demonstrated in laboratory assays using sediments from individual lakes (West et al. 2016). One recent review ofavailable data found that, on average globally, per-area CH4 fluxes are 8.0 times higher for eutrophic reservoirs
than for mesotrophic reservoirs, which in turn have CH4 fluxes that are, on average, 1.7 times as high as thosefrom oligotrophic systems (Deemer et al. 2016). Therefore, when possible, we recommend that countries include
an estimate of trophic status in their estimates of reservoir CH4 emissions allowing adjustment of emission factors
at Tier 2. Trophic status designation is generally achieved using either total phosphorus or chlorophyll a data andlatitude-specific classification cut-offs (Carlson 1977).
It has been suggested that eutrophication can enhance CO2 uptake and burial (Pacheco et al. 2015), but there is noevidence that this occurs consistently, and, when it does occur, the magnitude of this effect on CO2 is generally
much smaller (in overall greenhouse gas flux terms) than the effect of eutrophication on CH4 emissions (Deemer
et al. 2016).

Estimating the indicative anthropogenic component of total emissions
Estimation of the indicative anthropogenic component of total emissions or removals reflects the changes ingreenhouse gas fluxes to the atmosphere resulting from the landscape transformation into a reservoir or otherflooded lands. Unmanaged wetlands (e.g. peatlands) emit CH4 and sequester soil carbon and unmanaged lakes canalso be a source of CH4 prior to their conversion to a reservoir, but these are not estimated in national greenhouse

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gas inventories. The calculations allow for estimation of the anthropogenic component of emissions when theseunmanaged lands are converted to a reservoir by only considering the flooded land that was not previously
unmanaged lakes or wetlands. Box 7A.1 describes the general approach for estimating anthropogenic emissions,based on the area of Managed Land and unmanaged non-Wetland categories, which is used in this Guidance.
BOX 7A.1 (NEW)APPROACH FOR DEVELOPING INDICATIVE ESTIMATES OF THE ANTHROPOGENIC COMPONENT OF TOTALEMISSIONS FROM FLOODED LAND

The diagram below shows the rationale for indicative estimation of the anthropogenic component of
total emissions using the example of CH4 and CO2 fluxes from a reservoir where land is either
unmanaged (left) or managed (right) prior to flooding. CH4 and CO2 fluxes after flooding are shown(green arrows) compared to before flooding and the anthropogenic component, the newly flooded
land (red arrows) for Flooded Land remaining Flooded Land (FLRFL) and Land converted to
Flooded Land (LCFL). CH4 emissions/removals from the original water surface area and fromunmanaged wetlands are not considered in this approach by subtracting their area from the total
surface area of the reservoir.
For estimating anthropogenic CO2 emissions/removals from the reservoir, CO2 fluxes fromunmanaged lands in both FLRFL and LCFL are assumed zero. Changes in soil carbon stocks during
the first 20 years after flooding (LCFL) are provided in the guidance. For both FLRFL and LCFL,
long-term CO2 fluxes arising from the decomposition of catchment-derived organic matter are
considered natural in this guidance and are not incorporated into the CO2 emission factors. For
managed land (e.g. forest, croplands or grasslands), CO2 and CH4 fluxes prior to flooding, guidanceis provided in other Chapters and not considered here.

7A.1.2 Reservoirs
Introduction
Correctly estimating the anthropogenic component of greenhouse gas emissions from reservoirs requires a carefulassessment of the source and fate of reservoir carbon fluxes as such estimates are prone to double counting andinappropriate attribution of fluxes to human activity (Prairie et al. 2017a). The greenhouse gas emission factors
from Flooded Lands presented in this methodology report are composited output from an empirical model (Prairie
et al. 2017b), developed and calibrated with field measurements from diverse types of reservoirs located in various
regions of the world (see section 7A.1.2.3 Data Sources). The model allows us to annualize emissions that areoften measured over short periods (e.g. during the ice-free period for boreal systems) and estimate changes inreservoir greenhouse gas activity that have been observed to occur as reservoirs age. We anticipate that the models
will continue to improve over time as more measurements are made and additional models become available.

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7A.1.2.1 D EVELOPING T IER 1 EMISSION FACTORS FOR CO 2 AND NON CO 2 EMISSIONS FROM FIELD MEASUREMENTS
Recent, largely overlapping, literature compilations of field greenhouse gas measurements from over 220 distinct
reservoirs (Deemer et al. 2016), (Prairie et al. 2017b) form the basis of the emissions factors listed in Tables 7.9
and 7.15. The field measurements are a mixture of diffusive CO2, CH4 diffusive and/or bubble emissions and, fora new but smaller subset, downstream emissions for either or both gases. The method used to estimate greenhousegas fluxes from reservoirs is critical because different techniques can give quite different flux estimates (Schubert
et al. 2012), (Deemer et al. 2016), and because techniques integrate spatial and temporal variability to different
degrees (Wik et al. 2016). Flux estimates used to derive reservoir EFs in Chapter 7 were attained in a variety ofways. For CO2, diffusive fluxes were estimated using near-surface concentrations in combination with a thinboundary layer model for the majority of systems (Deemer et al. 2016), floating chambers, or, in a minority ofcases, eddy flux measurements. For CH4, diffusive fluxes were estimated using near-surface concentrations in
combination with a thin boundary layer model or chamber flux measurements. Ebullition fluxes of CH4 were
estimated using inverted funnel traps and echo sounders. Combined ebullitive and diffusive CH4 fluxes were
estimated using floating chambers or eddy flux techniques, or a combination of available methods. Downstream
emissions for gases were available for only a subset of the studied reservoirs.
Deriving Emission Factors directly from the compiled data is subject to a number of assumptions that can lead topotential biases. First, it requires an assumption that sampled systems are statistically representative of overall
reservoir distribution, a potentially problematic assumption given that measurement campaigns may occur insystems and periods in time where or when greenhouse gas emissions are high (e.g. where CH4 bubbling is visible)
or low. Second, it assumes that sampling of reservoirs is representative in time, potentially leading to biases as
there is considerable evidence that greenhouse gas emissions decrease markedly as reservoirs age (Abril et al.
2005), (Barros et al. 2011), (Teodoru et al. 2012), (Serça et al. 2016).
The Emissions Factors from reservoirs presented for this methodology were derived from the application of theGreenhouse Gas Reservoir (G-res) model (Prairie et al. 2017b). The G-res model is currently the only easily andwidely applicable model and was developed to account for the potential biases described above. It uses empirical
relationships between environmental drivers and emissions to estimate reservoir greenhouse gas fluxes. Depending
on available input data, the G-res model can also be used to make Tier 2 or Tier 3 estimates.
The methodology used to develop the G-res model and its usage to estimate reservoir greenhouse gas emissions is
described in detail in (Prairie et al. 2017b) but, briefly, consists of the following steps:
1. Data annualization: field sampling campaigns reported in the literature are rarely carried through the entire
annual cycle. For this reason, greenhouse gas data obtained over sub-annual time periods were annualized bytaking into account the annual temperature cycle at the reservoir site and the known temperature dependenceof processes leading to the production of CO2 and CH4.
2. Identifying relationships between annualized flux estimates and environmental variables: environmental
characteristics for each reservoir where greenhouse gas fluxes have been measured were extracted using
available global databases (GIS layers) and used as input variables for predictive models with an elastic net
variable selection procedure. This statistical analysis of the relevant data yielded the following model equations:
EQUATION 7A.1 (NEW)CH4 DIFFUSIVE EMISSION (MG C M-2 D-1)

log 10 ( CH 4 _diff ) = 0.88( ±0.16) − 0.012( ±0.002) Age + 0.048( ±0.006) Tfactor + 0.61( ±0.706) log 10 ( pcAlittoral )EQUATION 7A.2 (NEW)CH4 BUBBLING EMISSION (MG C M-2 D-1)

log10 ( CH 4 _ebul ) =−0.99( ±0.63) + 0.049( ±0.011) Qrad + 1.01( ±0.028) log10 ( pcAlittoral )2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories

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EQUATION 7A.3 (NEW)CO2 DIFFUSIVE EMISSION (MG C M-2 D-1)
c1 + c2Tfactor − c3 log10 ( Age ) + c4 SOC + c5 log10 ( Ares )log10 ( CO2 _ diff ) ==c1 2.035 ± 0.19=
c2 0.033 ± 0.005=
c3 0.29 ± 0.06=
c4 0.00178 ± 0.006=
c5 0.076 ± 0.03

Where:

Age= G-res Reservoir age since construction, yr

Ares= G-res Surface area of reservoir, km2

pcA

littoral= G-res percentage of reservoir area, Ares < 3 m deep, %CH

4 _diff= Diffusive emission of CH4 used in G-res, mg-C m-2 d-1

CH 4 _ebul= Ebullitive (bubble) emission of CH4 used in G-res, mg-C m-2 d-1

CO2 _ diff

= Diffusive emission of CO2 used in G-res, mg-C m-2 d-1

Qrad= G-res mean daily solar irradiance, kWh m-2 d-1

SOC= G-res Soil organic carbon from (0-30 cm), kg m-2

Tfactor= G-res temperature factor derived from air temperature, °C

Here, Age is reservoir age (years since construction), pcA

littoralarea was operationally defined as the percent

reservoir surface area shallower than 3m as derived from modelled reservoir bathymetry, SOC is surface Soil
Organic Carbon (0-30cm), Tfactor is a temperature factor that corrects for the non-linearity in the temperature
response of CH4 emissions, and Qrad is the mean daily solar irradiance averaged over a latitude-dependent period(see G-res documentation for details), and Ares is reservoir area, the surface area of the reservoir (km2). Further
details on the statistical analysis, the input environmental variables, their definition and sources can be found in(Prairie et al. 2017b). All resulting empirical models (Equation 7A.1 to 7A.3) were statistically highly significant
and explained between 37 and 47% of the variation in the greenhouse gas flux component (log scale).
1. Application of the models to larger database:
The empirical models described above were applied to the larger Global Reservoir and Dam (GRanD) database,(Lehner et al. 2011a) consisting of 6684 reservoirs with capacity >0.1 Mm3 located worldwide as shown in the
map in Figure 7A.2. These reservoirs are estimated to comprise collectively over 75% of the global surface areaof reservoirs and are distributed in all climate zones (Table 7A.1, Figure 7A.2). The environmental variables
required by the models were extracted for each reservoir as previously described and were used as inputs inEquations 7A.1 to 7A.3 to estimate the various components of greenhouse gas emissions. In total, greenhouse gas
emissions could be estimated for more than 6000 reservoirs worldwide.

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Figure 7A.2 (New)

Location of the reservoirs in the GranD database and shadowgram of
their latitudinal distribution.

TABLE 7A.1 (NEW)NUMBER OF RESERVOIRS IN THE GRAND DATABASE IN EACH IPCC CLIMATE ZONE.
IPCC Climate zone

Number of Reservoirs

Boreal dry

3

Boreal moist

87

Cool temperate dry

333

Cool temperate moist

1746

Polar moist

27

Tropical dry

625

Tropical moist

793

Tropical montane

227

Tropical wet

126

Warm temperate dry

623

Warm temperate moist

2072

2. Derivation of CH4 Emissions Factors:
CH4 emission is the sum of reservoir-wide ebullitive and diffusive emissions (Equations 7A.1 and 7A.2). However,
because the diffusive component is not constant in time but declines with age, Equation A.1 was integrated toestimate the average annual emission over different periods. Based on the available literature, much of the initial
greenhouse gas pulse occurs within the first 20 years following impoundment and this time interval was assumed
to represent Land converted to Flooded Land. The emission factor of CH4 in this time interval can be derived with
Equation 7A.4. For Flooded Land remaining Flooded Land, the integration period was from 20 to 100 years postimpoundment. The emission factor of CH4 in this time interval can be derived with Equation 7A.5.

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EQUATION 7A.4 (NEW)EMISSION FACTORS FOR LAND CONVERTED TO FLOODED LAND

 20CHdAge
4 − diff∫0
EF=+ CH 4 −bubbling 


20



EQUATION 7A.5 (NEW)EMISSION FACTORS FOR FLOODED LAND REMAINING FLOODED LAND

 100CH∫ 4 _ diff dAge + CH=EF  20
4 _ bubbling


80


Where
EF

Emission Factor

CH 4 _ diff

Diffusive emission of CH4, Mg-C m-2 d-1

CH 4 _ bubbling

Ebullitive (bubble) emission of CH4, Mg-C m-2 d-1

Application of Equations 7A.4 and 7A.5 to the reservoirs described in Table 7A.1 were averaged according theaggregated climate zones defined in Table 7A.2 to produce the final Emission Factor (EF) tables for Flooded Land
Remaining Flooded Land (Table 7.9) and Land Converted to Flooded Land (Table 7.15). Emissions factors (EFs)are expressed as kg CH4 ha-1 yr-1.
In addition to the diffusive and ebullitive emissions from reservoir surfaces, downstream CH4 emissions are
estimated. These downstream emissions are estimated by multiplying reservoir emissions by a fraction (Rd), whichis the ratio of total CH4 emissions (kg CH4-C y-1) downstream of the reservoir (i.e. degassing at the dam andemissions from the downstream river) to CH4 emissions from the surface of the reservoir (diffusion + ebullition;
kg CH4-C y-1). Downstream emissions are influenced by local climate, reservoir morphology, and design featuresof the dam and spillway (Deemer et al. 2016). In general, these emissions will be large in thermally stratified
reservoirs with anoxic, CH4-rich bottom waters and hypolimnetic withdrawal (dos Santos et al. 2017). Theseemissions can be further enhanced by high air-water gas exchange rates at the dam or spillway that promote therapid evasion of CH4 to the atmosphere before it can be oxidized to CO2 in the downstream river (Abril et al. 2005).
Accurately predicting downstream emissions requires detailed knowledge of dam design (i.e. withdrawal depth)
and operating conditions (i.e. withdrawal rates) and is beyond the scope of the Tier 1 methodology. However, if
appropriate at a higher tier, downstream emissions may be estimated using climate zone specific Rd values in Table
7.10 derived from a literature compilation listed in section 7A.1.2.3 Data Sources.
Downstream emissions have received much less attention than emissions from reservoir surfaces, but have beenreported for 36 reservoirs distributed across the 6 aggregated IPCC climate zones (see section 7A.1.2.3 Data
Sources, Table 7A.5). It should be noted, however, that reported downstream emissions can be biased high or low,depending on study-specific methodological details. For example, several studies assumed that all excess dissolved
CH4 (i.e. the difference between actual dissolved CH4 concentration and atmospheric equilibrium) entering thedam would evade to the atmosphere via a combination of degassing at the dam and diffusion from the river surface(Beaulieu et al. 2014a), (Teodoru et al. 2012). This approach will overestimate downstream emissions because up
to 85% the CH4 that enters the downstream waterbodies can be oxidized to CO2 (Kemenes et al. 2007). Other
studies only reported degassing in turbines (i.e. did not estimate downstream waterbody emissions), thereby
biasing downstream emissions low (Maeck et al. 2013). Although methodological differences can bias
downstream emission values, the effect of methodology was not apparent in the pooled data, likely because otherfactors, such as the depth of water withdrawal relative to the oxycline, were more important drivers. Similarly,
differences among climate zones were not apparent in the data, therefore the Tier 1 Rd value was not disaggregatedby climate zone. Due to the highly skewed distribution of reported Rd values, the Tier 1 Rd value is based on the
median value (see 7A.1.2 “Validation of the data-model approach”). At the Tier 2 level the downstream emission
term in Equation 7.10 can be set to zero in reservoirs where epilimnetic water is withdrawn and discharged to theriver downstream. Countries can directly measure downstream emissions at the Tier 3 level using the methods
discussed in the references cited in section A7.1.2.3 Data Sources (Table A5).

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3. Grouping of reservoirs according to IPCC climate zones
The 6014 estimates of CH4 emissions (diffusive + ebullitive) from worldwide reservoirs generated by the G-res
tool were grouped according to the IPCC climate regions. A regression tree approach was used to lump certain
climate categories together based on their abilities to separate groups with different CH4 emissions. The final
grouping comprised 6 aggregated climate zones (Table 7A.2) and these were applied throughout this Methodology
Report.
TABLE 7A.2 (NEW)AGGREGATED CLIMATE ZONES BASED ON DIFFERENCES IN CH4 EMISSIONS BETWEEN CATEGORIESIPCC Climate zone

Aggregated climate zone

Boreal dry
Boreal moist
Polar dryBorealPolar moist
Cool temperate dry
Cool temperate moist

Cool temperate

Warm temperate dry

Warm temperate dry

Warm temperate moist

Warm temperate moist

Tropical dry
Tropical montane
Tropical moist
Tropical wet

Tropical dry/montane
Tropical moist/wet

Validation of the data-model approach
Surface Emissions
Model estimations and direct measurements are not strictly comparable in that the former have been annualized
and represent the integrated average annual emissions of the first 20 years post-impoundment (plus ebullitive
emissions) while the latter are point measurements encompassing varying degrees of spatial and temporal
integration depending on the study. Nevertheless, it is informative to compare the central tendency and variability
in CH4 emissions among reservoirs in each of the climate zones. Both model estimations and field measurements
were highly variable and positively skewed in each climate zone (Figure 7A.3).

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Figure 7A.3 (New)Box plots of model estimates (empty) and Field measurements (filled)of CH 4 emissions (note logarithmic scale) in aggregated IPCC climate
zones.

Field measurements are from (Deemer et al. 2016) while modelled estimates are derived from G-res model applied
to about 6000 reservoirs worldwide. Exact correspondence between measured and modelled ranges is not expected
given that the models were applied to a large number of reservoirs of different configurations. Numbers in box
plots correspond to the number of observations in each climate zone.
While the distribution of modelled and measured greenhouse gas emission estimates generally overlapped in eachclimate zone, a more direct measure of correspondence is shown by the relationship between field measurements
versus model estimates of CH4 emissions (Figure 7A.4). CH4 emissions from individual reservoirs predicted using
the Tier 1 approach agreed reasonably well with measured CH4 emissions (Nash-Sutcliffe Efficiency: 0.8, with nodetectable bias in either slope or intercept of least-squares regression; Figure 7A.4). These comparisonscollectively provide evidence that the model estimates capture both the variability and central tendency in CH4emission rates.

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Chapter 7: Wetlands

Figure 7A.4 (New)Comparison of measure CH 4 emissions with estimates based on the
Emission Factors (EFs, Tables 7.9 and 7.15) of Tier 1 methodology.

Figure 7A.4 re-drawn using final approved Tier-1 method. NSE=0.83; no evident bias for any climate category.
No chlorophyll correction used (alpha=1 in all cases). 1:1 line (black), best-fit linear regression line (blue) with
95% confidence intervals for slope (grey shading) are shown.
Downstream Emissions
Downstream emissions estimated using the median of the literature Rd values (0.09), combined with model
estimated surface emission rates, agree well with observed downstream emission rates (Figure 7A.5). Downstream
emissions estimated using the mean Rd literature value (0.60) systematically overestimate downstream emissions(Figure 7A.5), lending additional support for the use of the median Rd value for estimating downstream emissions.

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Figure 7A.5 (New)Measured downstream (DN) CH 4 emissions compared to model
estimates.

The left and right panels model downstream emissions using the median and mean Rd values collected from theliterature, respectively. Because using the mean produced consistent overestimates (right panel), the use of themedian is preferred.

7A.1.2.2 CO 2 EMISSION FACTORS FOR L AND C ONVERTED TO
F LOODED L AND .
The creation of reservoirs as well as other Flooded Lands often involves the flooding of terrestrial ecosystems andtheir organic matter pools. A portion of these pools is rapidly degraded by microbial activity generating a CO2
pulse that diminishes steadily during the 10-20 years following flooding until the Flooded Land attains a new
steady state emission rate (Abril et al. 2005), (Barros et al. 2011), (Teodoru et al. 2012). The new steady state
emission rate generally falls in the range typical of other freshwater ecosystems that have remained flooded for >20 years (Prairie et al. 2017b). Meta-analyses of published emission studies (Barros et al. 2011), (Prairie et al.
2017b) suggest that the rate of decline decreases with time (faster in the early years, slower later on) and that thetemporal evolution of CO2 emissions is expressed as a general negative power function. The literature suggeststhat a decade is a realistic period for the return to a quasi-equilibrium (e.g.(Tremblay et al. 2005), reflecting the
new balance between primary production and respiration of the reservoir ecosystem. A more conservative
approach assumes, instead, that this new equilibrium is reached only after 100 years - a value that is often used torepresent the expected lifetime of reservoirs in life-cycle analysis (e.g. (Gagnon et al. 2002). Over such a period,
integration of the emissions above the modelled new equilibrium value at 100 years (upper panel of Figure A6)
suggests that about 75% of the cumulative CO2 flux is natural, i.e. that only 25% can be considered the result of
the impoundment process (Prairie et al. 2017a).
The carbon stocks of the land prior to impoundment are specific for each land use / land cover, and the default
Tier 1 estimates for these pools can be derived from the 2006 IPCC Guidelines, FAO 2017 database as refined inthis volume, and the 2013 Wetlands Supplement, while masses for dry matter in undrained and drained peatlands
are given in the 2013 Wetlands Supplement Table 2.6. The guidelines recognize five terrestrial C pools: aboveground biomass, below-ground biomass, dead wood, litter and soil organic matter. In preparation of theimpoundment area, the carbon losses from harvested biomass and the emissions from deliberately burned biomass
are reported according to the 2006 IPCC Guidelines as refined in this volume. The CO2 emissions from the decayof dead organic matter in the newly flooded land is described below.
The easily decomposable organic matter fractions (litter, foliage, twigs, fine roots, organic soils) contribute to thepost-flooding CO2 pulse, while the more recalcitrant fractions (tree boles, mineral soils) are for the most partpreserved. However, it is noteworthy that following flooding, the mineral soil layer rapidly becomes (and remains
indefinitely) anoxic below a depth of a few mm (Lorke et al. 2003). Anaerobic remineralisation occurs very slowly
and below this depth, organic carbon can be considered permanently buried for practical inventory estimation
purposes. In organic soils and in humus layers, flooding may produce an analogous anaerobic zone. In thermallystratified reservoirs, mineralisation of organic matter will be retarded in anoxic hypolimnia.

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Chapter 7: Wetlands

The surge in CO2 emission post-flooding is caused by the remineralisation of pre-flooding organic matter pools
and it can be considered as a net loss of the carbon stock from the previous land use. At the moment, there is little
information to quantify how individual terrestrial organic carbon pools contribute to the post-flooding CO2 surge.
Nevertheless, the abundant amount of reservoir emission measurements for young (< 20 y) reservoirs (Deemer et
al. 2016) has made possible the development of models such as G-res that can be used to estimate net post-flooding
CO2-C emissions (Table 7.13).
The approach used to derive net CO2 emissions from reservoirs is the same as that used to derive emissions of CH4(section 7A.1.2.1) and is based on the greenhouse gas reservoir (G-res) model (Prairie et al. 2017b) which uses
empirical relationships between environmental drivers and greenhouse gas emissions to estimate reservoir
greenhouse gas fluxes from a large, diverse set of reservoirs (>6000 reservoirs with global distribution).
Instantaneous greenhouse gas flux measurement data are annualized to take into consideration seasonal changes
in temperature that may be different from the moment when empirical measurements were conducted in the field.
An example where annual fluxes are generated from point measurements is described in the technicaldocumentation of the IHA G-Res tool (Prairie et al. 2017b). There are two approaches to derive emissions. In one,a power function for annual flux, CO2 = C ∙ Age-b where C is a reservoir specific constant depending on nutrients,
temperature, reservoir area etc. and b is estimated by fitting to the data, is assumed to reach the natural equilibrium
level of CO2 flux at the reservoir age of 100 years. That level determines how much of the annual CO2 flux should
be subtracted each year from the integrated area under the flux CO2 curve, see (Prairie et al. 2017a). Anotherapproach, which is applied to derive Tier 1 emission factors, uses an empirical relationship between the derived
integrated decay curve and soil organic carbon stock as well as climate under the newly flooded area (Fig. 7A.6
and Equation 7A.3). The emissions attributable to the creation of the reservoir over a 100-year period are reported
as a constant rate over the first 20 years post-flooding. Accordingly, the rates of emissions are dependent on climate
and soil C content (to 30 cm depth) for the flooded area (see text in 7A.1.2 and Equation 7A.3 and section 7.3.2,
Equation 7.14).
Figure 7A.6 (New)

Relationship between CO 2 surge estimates from the newly flooded
lands using the decay curve approach and the flooded soil organiccarbon stock approach.

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Volume 4: Agriculture, Forestry and Other Land Use

7A.1.2.3 D ATA SOURCES
Data sources and range of emission values (mg C-CH4 m-2 d-1) for directly measured CH4 emissions are in Table
7A.3. Data sources used to develop models (Equations 7A.1, 7A.2 and 7A.3) are largely overlapping and are inAnnex VI of Prairie et al. 2017b. These were used in section 7A.1.2.2 of this Annex to validate the Emission
Factors provided in Tables 7.9 and 7.15.
Data sources (including systems assessed and citations) for estimating the multiplier (RD, Table 7.10) which is theratio of total CH4 emissions (kg CH4-C yr-1) downstream of the reservoir (i.e. degassing at the dam and emissions
from the downstream river) to CH4 emissions from the surface of the reservoir (diffusion + ebullition; kg CH4-C
yr-1) are in Table 7A.4.
TABLE 7A.3 (NEW)DATA SOURCES USED FOR MODELLING CH4 EMISSIONS FROM RESERVOIRS WITHIN DIFFERENT CLIMATE ZONES.
Grouped
IPCC
Climate
Zone
Polar moist,
boreal dry
and moist
Cooltemperate
moist and
dry*

Warm
temperate
moist

Tropical dry
andmontaneTropical wet
and moist

7.42

Number ofsystems with CH4
measurements in
category

6

16

14

13

26

Range of reported
emissions values(mg C-CH4 m-2 d-1)

References

0.4-13(Tremblay et al. 2005), (Teodoru et al. 2012), (Demarty et al.
2011), (Demarty et al. 2009), (Brothers et al. 2012), (Kelly et al.
1994), (Roehm & Tremblay 2006), (Tadonléké et al. 2012),(Duchemin et al. 1995), (Huttunen et al. 2002), (Fedorov et al.
2015)

0-360.7(Harrison et al. 2017), (Matthews et al. 2005), (Hendzel et al.
2005), (Venkiteswaran Jason et al. 2013; Venkiteswaran et al.
2013), (Kelly et al. 1997), (Deemer et al. 2011), (Maeck et al.
2013), (Huttunen et al. 2002), (Gruca-Rokosz et al. 2011),(Gruca-Rokosz et al. 2010), (Beaulieu et al. 2014a), (Beaulieu etal. 2014b)

2.5-176.0(Rosa et al. 2004), (dos Santos et al. 2006), (Harrison et al.
2017), (Li et al. 2015), (Maeck et al. 2013), (Gruca-Rokosz etal. 2010), (Zhao et al. 2013), (Wu 2012), (Yang et al. 2013),(Chen et al. 2011), (Lu et al. 2011), (Zhen 2012), (Xiao et al.
2013), (Zhu et al. 2013), (Zhao et al. 2015), (Li et al. 2014),(Bevelhimer et al. 2016), (Mosher et al. 2015)

0.5-582.3(Diem et al. 2012), (Ometto et al. 2013), (Pacheco et al. 2015),(Roland et al. 2010), (Sturm et al. 2014), (DelSontro et al.
2011), (Selvam et al. 2014), (Bansal et al. 2015), (DelSontro etal. 2010), (Eugster et al. 2011), (Kumar & Sharma 2012),(Teodoru et al. 2015), (Almeida et al. 2016)

3.6-258.3(Therrien et al. 2005), (Tremblay et al. 2005), (Bergström et al.
2004), (Guérin et al. 2006), (Kemenes et al. 2007), (Kemenes etal. 2011), (Musenze et al. 2014), (Rosa et al. 2004), (dos Santos
et al. 2006), (St. Louis et al. 2000), (Ometto et al. 2013),(Bergier et al. 2011), (Duchemin et al. 2000), (Roland et al.
2010), (Keller & Stallard 1994), (Joyce & Jewell 2003), (Selvam
et al. 2014), (Deshmukh 2013), (Deshmukh et al. 2014), (Abrilet al. 2005), (Rosa et al. 2003), (Lima 2005), (Lima et al. 2002),(Lima et al. 1998), (Marcelino et al. 2015)2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories

Chapter 7: Wetlands

TABLE 7A.4 (NEW)RESERVOIRS AND CITATIONS FOR MEASURED RD VALUESSystem Name

IPCC climate zone

*Citation

Eastmain-1

Boreal(Teodoru et al. 2012)

Gruyere, Lake Grimsel, Lake
Luzzone, Lake Sihl, Wohlen, Serrig,
Dworshak

Cool temperate(Diem et al. 2012), (DelSontro et al. 2016),(Maeck et al. 2013), (Soumis et al. 2004)

F.D. Roosevelt, New Melones,
WallulaWarm temperate dry(Soumis et al. 2004)

William H Harsha Lake, Allatoona,
Douglas, Fontana, Guntersville,
Hartwell, Watts Bar, Eguzon, Oroville,
ShastaWarm temperate moist(Beaulieu et al. 2014b), (Bevelhimer et al. 2016),(Descloux et al. 2017), (Soumis et al. 2004)

Lake Kariba, Xingó, Tehri

Tropical dry/montane(DelSontro et al. 2011), (dos Santos et al. 2017),(Kumar & Sharma 2016)

Nam Leuk, Nam Ngum, Funil, Itaipu,
Segredo, Serra da Mesa, Três Marias,
Petit Saut, Koombooloomba, Nam
Theun 2, Tucuruí, Samuel, Balbina

Tropical moist/wet(Chanudet et al. 2011), (dos Santos et al. 2017),(Abril et al. 2005), (Bastien & Demarty 2013),(Deshmukh et al. 2016), (Serça et al. 2016),(Guérin et al. 2006), (Kemenes et al. 2007)*See references section for full citations.

7A.1.3 Other constructed waterbodies (agricultural ponds,
aquaculture ponds, canals and ditches)
Many forms of agricultural and silvicultural land management involve the creation of artificial waterbodies. For
example, ditches are often used for land drainage or irrigation; small constructed ponds are used for small scale
irrigation or as a water source for livestock; and canal systems are used for water level management, water transfers
and navigation. Aquaculture ponds and flooded pastures can occupy extensive areas on the landscape (Yang et al.
2017), (Kroeger et al. 2017). In settlements ponds may be created for recreation, aesthetics or stormwater
management.
Similar to reservoirs, CO2 emissions from smaller volume constructed waterbodies including ditches, canals, farm
ponds and aquaculture ponds, are the result of decomposition of soil organic matter and other organic matter within
the waterbody or entering the water from the catchment, as well as from biological components (e.g. fish). No
guidance is provided here since these emissions are either estimated elsewhere (e.g. as soil carbon loss) or represent
short-term natural carbon cycling (e.g. biological turnover).
CH4 emissions from small constructed waterbodies are primarily the result of new methanogenic production of
CH4 induced by anoxic conditions, which occurs when waterbodies have high organic matter loading and low
oxygen status. These conditions often occur in small constructed waterbodies, such as slow-flowing ditches (Evanset al. 2016), agricultural ponds (Selvam et al. 2014) and aquaculture ponds (Robb et al. 2017), but may be lower
where mixing or aeration occurs as part of aquaculture management (e.g. (Vasanth et al. 2016) and are sensitive
to temperatures (Davidson et al. 2011). Area-specific emissions from these constructed waterbodies may equal or
exceed those observed in small lakes and reservoirs (Bastviken et al. 2010); see above). Furthermore, the CH4
emissions from small constructed waterbodies are a direct consequence of the construction of the waterbody.
CH4 emission factors from small constructed waterbodies (Section 7.3.1.2, Table 7.12) are based on review of thepeer reviewed literature using appropriate search terms. Literature was obtained using Web of Science and Google
Scholar. In some cases (e.g. PhD Theses), data were obtained directly from authors. For each study or sites withinstudies, a mean CH4 flux was extracted from tables, figures or text. Fluxes were converted to annual fluxes bysimple scaling (e.g. multiplying per day rates by 365 days), or if more information was provided (e.g. days per
aquaculture production cycle and production cycles per year), data were annualized using this additional
information. Methane emissions from land and water surfaces are rarely normally distributed within datasets dueto the heterogeneity of emission pathways and controlling factors, and data were therefore log-transformed during
the calculation of mean emission factors. The high variability and relatively small number of observations alsoprecluded estimation of separate Tier 1 EFs by climate zone or other factors (apart from waterbody type and (forponds) salinity), and 95% confidence intervals are correspondingly large.

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Volume 4: Agriculture, Forestry and Other Land Use

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