Methane Emission from Wetlands of India

May 28-30, 2018

J.K. Garg uru Gobind Singh Indraprastha University

New Delhi 110078, India

SARI Workshop on LULUC of South/Southeast AsiaQuezon City, Manila, Philippines

jkgarg@ipu.ac.in

Ramsar Convention (1971) usesa broad definition of wetlands,including the lakes and rivers,swamp and marshes, wetgrasslands and peatlands,estuaries, deltas and tidal flats,near-shore marine areas,mangroves and coral reefs, andman-made sites such as fishponds, rice paddies, reservoirsand salt pans.

WetlandsWetlands are multi-use, multifunctional dynamic ecosystems.

Wetlands are a rich repository of biodiversity and provide myriad ecosystem services.

Wetlands are sources, sinks as well as transformers of carbon dioxide and other green house gases such CH4 and N2O.

Wetlands are significant source (about one third) of Methane (28 GWP), most important Green House Gas after CO2.

Very few systematic studies carried out for methane emission from wetlands in the tropical countries

CH4 has shown maximum percentageincrease of 150% (722-1803 ppb) ascompared to CO2 (40%; 278-390.5 ppm)and N2O (20%; 271-324.2 ppb) during thetime interval of 1750-2011 (Ciais et al.,2013).

Methane (CH4) is considered as one of the mostimportant GHG as it has higher volume of emissionsthan any other gas except CO2 and exhibits 28 timeshigher global warming potential than CO2 (Myhre etal., 2013).

NOAA 2017

Bridgham, et al. 2013

Methane emission from wetlands Depends on:• Wetland area• Macrophytic vegetation/ productivity• Temperature• Wetland condition, besides existence of anaerobic conditions

Remote sensing can provide Information on• Wetland area• Macrophytic vegetation• Temperature

Very few studies have been carried out using geospatial tools to assess CH4

emissions at national and international scales.

Mitsch et. al (2012)

Methane Emission and Wetlands – Some Issues

1. No universal accepted definition of wetlands.2. Wetlands are highly dynamic ecosystems; no seasonal estimate of global

area under wetlands available.3. Methane emission depends on existence of anaerobic conditions and

productivity of wetland in question.4. Methane emission further complicated by hydrology, water quality and

temperature.5. Global Warming Potential – figures varies from 21 - 45.6. ------------------------------

1. Very few studies on methane emission from wetlands carried out in India.2. Most of the studies are small area/point studies and have only local

applicability, primarily due to difficult conditions in contrast to studies onpaddy rice.

3. Due to variability in climatic conditions and rainfall pattern across the countryno single emission factor likely to give reasonably good estimates ofmethane emission from wetlands.

4. Very few studies using geospatial techniques carried out (Agarwal andGarg, 2008; Bansal et al. 2017).

5. Estimates based on IPCC Guidelines give very high estimates which are farfrom the actual emissions.

Methane Emission from wetlands - Studies in India

Studies carried out in India

• Research Publications

– Field based studies: 8

– Modelling: 1

– RS/GIS based studies: 9

Methane emission modeling (using geospatial techniques)

Total CH4 emission from wetlands was estimated using Semi – automated EmpiricalMethane Emission Model (SEMEM). SEMEM model estimates the total CH4 emissionsusing the following equation (Agarwal and Garg, 2007; Liu, 1996):

PAFEE tobsCH ...4 =where,

ECH4 = Total amount of CH4 emittedE obs = Observed CH4 fluxA = Wetland AreaFt = Temperature FactorP = Productivity Factor (derived from literature)

Wetlands and Green House Gas Emissions- CH4First Study – Agarwal and Garg, 2009

MODIS data

Geo-referencing

NDVI (using 1&2)

Bowtie Correction

Bands 1,2 and 3

Stacking

LST

Knowledge based Classification

2nd phaseInput: Classified

and Ft, productivity and flux

1st phaseInput: LST

Model

Bands 31 and 32

Output: Ft

Output: Emitted Methane image

Class wise methane emission

Literature

FluxProductivity

3rd phase:Input: classified and methane emission

image

METHANE EMISSION - INDIA

Months Methane Emission

(Tg)January -

March0.477

April - June 0.719

July -September

0.712

October -November

1.070

Total Wetland Area : 8.82 mhaAnnual Methane Emission : 2.645 Tg

Wetland estimates based on Resourcesat- AWiFS (2004-05)

Comprehensive Study: RS/GIS + Field basedKeetham Lake Nawabganj Lake

Okhla Reservoir

CH4 gas samples were collected zone-wise i.e., for shallow water zone (SWZ) , deep water zone (DWZ) and exposedwetland soil zone (EWSZ) using the Semi-Static Chamber Technique season-wise i.e., for monsoon (July-October),winter (November-March) and summer (April-June).

CH4 gas samples were analyzed using gas chromatograph (model no. 6890, Agilent Technologies, USA).

23°45’-30°30 N77°-84°45 E Area 24170’

thousand ha

Salient features of study sites

Site Coordinates WetlandType

Area (ha) Flowing/Static

Annual water depth range (m)

Vegetation Density

Name of associated Bird Sanctuary/District

Keetham Lake

27° 15.287’ N77° 50.386’ E

Natural 403 Flowing 0.15 – 8 Sparse Soor Sarovar Bird Sanctuary, Agra

Nawabganj Lake

26° 37.094’ N80° 39.259’ E

Natural 225 Static 0.15-1.92 Dense Nawabganj Bird Sanctuary, Unnao

Okhla Reservoir

28°33.71’ N77°18.33’ E

Man -made

400 Semi-static

0.15 -3 Intermediate Okhla Bird Sanctuary, Gautam BudhNagar

Methodological Framework

Collection and analysis different water, soil and vegetation parametersParameters Analytical technique usedWater DO, Eh and pH of soil and water Portable DO, Eh and pH Meter (HACH-HQ30D)

Water and Soil Temperature Portable Infra Red Thermometer (OAKTON: Infra Pro 5)

Water Phosphate Stannous Chloride Method (APHA, 1995)Water and Soil Nitrate Phenol Di-Sulphonic Acid (APHA, 1995)Water and Soil Sulfate Turbidimetric Method (APHA, 1995)Water Depth Well marked wooden-poleWater BOD Modified Winkler Method (APHA, 1995)Soil Available Phosphorus P. Olsen Method (Olsen et al., 1954)Soil Moisture Oven Drying Method (Singh et al., 1999)Soil Organic Carbon Walkley and Black Method (Walkley and Black, 1934)Plant Biomass Harvest Method (APHA, 1995) Soil Texture Bouyoucos Hydrometer Method (Singh et al., 1999)

Point CH4 flux vis a vis wetland structural components

Annual mean CH4 flux (mg m-2 d-1)

2010-2011 Keetham lake Nawabganj lake Okhla Reservoir

Shallow water zone (SWZ) 122.3 ± 20.0 (n=20)* 300.1 ± 62.9 (n=18) 209.8 ± 39.5 (n=24)

Deep water zone (DWZ) 17.3 ± 3.1 (n=12) 146.6 ± 18.9 (n=18) 23.3 ± 2.5 (n=15)

Exposed wetland soil zone (EWSZ) 75.7 ± 18.7 (n=22) 56.7 ±11.7 (n=26) 61.1 ± 13.4 (n=22)

Net CH4 flux (mg/m2/day) 80.0±11.8 (n=54) 153.5 ± 23.2 (n=62) 110.32 ± 19.2 (n=61)

2011-2012 Keetham lake Nawabganj lake Okhla Reservoir

Shallow water zone (SWZ) 137.3 ± 15.8 (n=20)* 303.6 ± 64.7 (n=22) 115.9 ± 10.5 (n=24)

Deep water zone (DWZ) 26.5 ± 6.1 (n=14) 151.2 ± 23.3 (n=20) 38.9 ± 6.8 (n=10)

Exposed wetland soil zone (EWSZ) 107.62 ± 22.2 (n=24) 91.2 ±23.0 (n=24) 101.7 ± 18.6 (n=28)

Net CH4 flux (mg/m2/day) 98.3±12.1 (n=58) 180.2 ± 26.4 (n=66) 97.08 ± 9.9 (n=62)

* n represents the sample size for each respective zone

Sampling Year/Seasons CH4 flux (mg m-2 d-1)

2010-2011 Keetham lake Nawabganj lake

Okhla Reservoir

Observed CH4 flux

Monsoon 47.00 90.67 50.37 62.68

Winter 30.56 66.31 32.82 43.23

Summer 159.31 319.06 157.25 211.87

2011-2012 Keetham lake Nawabganj lake

Okhla Reservoir

Monsoon 61.96 104.91 77.29 81.38

Winter 39.24 70.05 44.78 51.36

Summer 189.76 427.82 151.38 256.32

Observed mean CH4 (Eobs) flux used for upscaling/modeling of CH4 for Uttar Pradesh

Satellite data used for estimation of Area-wise seasonal integrated CH4 flux (ASIF)

Scene No. Site Name Satellite-

Sensor Date of Acquisition Path-Row

Subscene Season

1 Keetham Lake RS2-LISS IV 18th November 2011

97-52 C Winter

2 Keetham Lake RS2-LISS IV 28th May 2012 97-52 C Summer

3 Nawabganj Lake RS2-LISS IV 22nd December 2011

99-53 B Winter

4 Nawabganj Lake RS2-LISS IV 13th May 2011 99-53 B Summer

5 Okhla Reservoir Google Earth 24th January 2012 -- -- Winter

6 Okhla Reservoir RS2-LISS IV 03rd May 2011 96-51 C Summer

Wetland area estimation using MODIS data

MODIS (Moderate Resolution ImagingSpectro-radiometer) data utilized for mappingand delineating the wetland areas due to itswide swath and area coverage.

As MODIS data has inter-band correlation andhigh data dimensionality leading to thespectral mixing of the features, three datamining techniques viz. Principal ComponentAnalysis (PCA), Band to Band Correlation(BTBC) analysis and Stepwise DiscriminantAnalysis (SDA) were applied to extractoptimal bands and indices to reduce the datadimensionality.

Wetland Feature AWiFS Area (October-November 2010)

MODIS Area (October -2010) Correction Factor

Open water 1612.52 NA -Aquatic vegetation 1690.05 NA -Net wetland area 3302.57 1804.63 1.83

Season Sampling Year2010-2011 2011-2012

MODIS Area Corrected Wetland Area

MODIS Area Corrected Wetland Area

Monsoon 1804.63 3304.57 1946.76 3562.68Winter 1462.33 2676.14 1528.22 2796.73Summer 935.17 1711.41 984.16 1801.07Net wetland area per year 1400.71 2564.04 1486.38 2720.16

Wetland area (km2) estimated for the state of Uttar Pradesh using MODIS data

Comparison of wetland area (km2) estimated for the state of Uttar Pradesh using AWiFS and MODIS data for 2010

*Due to the non-availability of MODIS data for monsoon season owing to cloud cover, MODIS data available for themonth of October has been used to estimate CH4 emitting wetland areas for monsoon season

Temporal variations in wetland area (km2) 2010-11 2011-12

The effect of temperature on methane flux was assessed by remotely sensed temperature factor (Ft )which is analogous to Q10 and can be defined as the rate of change of methane emissions in response tochange in temperature. To assess the dependency of CH4 emissions on temperature for each season ateach site during both the sampling years, wetland surface temperature and Ft have been calculated fromMODIS Land Surface Temperature (MOD11_L2) product using the equation (Liu, 1996)

Ft =

where, Ft = Temperature factor generated for each pixel in a MODIS LST image, Modeled temperature for each pixel in a MODIS LST image calculated using following equation:

F(TS) =

where TS = surface temperature for each pixel in MODIS LST image and is mean of F(TS) for all pixels of UP LSTimage of MODIS

Wetland Surface Temperature

Ambient Air Temperature (°C) and MODIS Surface Temperature (°C) for Wetland and Non-Wetland Areas

*Ambient Air Temperature was recorded at the time of sampling using Portable Thermo Recorder – TR 73 U**In-situ temperature values for wetland areas were calculated by averaging the seasonal temperature valuesrecorded for three representative wetlands (Keetham lake, Nawabganj lake and Okhla Reservoir) using PortableInfra Red Thermometers (OAKTON: Infra Pro 5)

Major Wetland Group Wetland Types Productivity factorI. Lakes/Ponds, Ox-bow lakes/Cutoff Meanders,

Reservoirs, Tanks, Waterlogged areas,Abandoned Quarries, Ash Pond/Cooling Pond,Wetlands smaller than minimum mappingunits.

0.25 (high altitudes)0.50 (Rest of India )

II. Swamp/Marsh 0.25 (high altitudes)0.50 (Rest of India)

III. Estuary, Lagoon, Creek, Tidal Flat/Mud Flat,Coral Reef, Salt Marsh

1.00 ?

IV. Mangroves 1.00

Wetlands and modified productivity factors

Source: Garg et al. (2005) – based on literature

Methane emission modeling (using geospatial techniques)

Total CH4 emission from wetlands was estimated using Semi – automated Empirical MethaneEmission Model (SEMEM). SEMEM model estimates the total CH4 emissions using thefollowing equation (Agarwal and Garg, 2007; Liu, 1996):

PAFEE tobsCH ...4 =where,

ECH4 = Total amount of CH4 emittedE obs = Observed CH4 flux calculated in fieldA = Wetland Area estimated using MODIS dataFt = Temperature Factor estimated using MODIS dataP = Productivity Factor (derived from literature)

Season Observed CH4 flux (kg/km2/day)

Methane-emitting area (km2)

Wetland Surface Temperature (ºc)

Estimated CH4emissions (Gg per season)

Estimated CH4emissions (Tg per season)

Monsoon 62.28 3304.57 29.62 26.88 0.0269Winter 42.23 2676.14 23.76 16.04 0.0160Summer 211.87 1711.41 33.15 47.56 0.0476

Total 317.78 2564.04 28.84 90.48 Gg/yr 0.0905 Tg/yr

Estimated CH4 emissions for Uttar Pradesh (2010-2011)

Season Observed CH4 flux (kg/km2/day)

CH4 -emitting area (km2)

Wetland Surface Temperature (ºc)

Estimated CH4emissions (Gg per season)

Estimated CH4emissions (Tg season-wise)

Monsoon 81.38 3562.68 30.23 37.45 0.0375Winter 51.36 2796.73 24.06 18.77 0.0188Summer 256.32 1801.07 39.20 61.39 0.0614

Total 389.06 2720.16 31.06 117.61 Gg/yr 0.1177 Tg/yr

Estimated CH4 emissions for Uttar Pradesh (2011-2012)

Temporal variations wetland area (km2) - UP Temporal variation in wetland surface temperature (°C)

Temporal variations in estimated CH4 emissions (Gg/yr) from wetlands - UPS

a) b)

Percentage of total wetland area and Estimated CH4 emissions for different regions of Uttar Pradesh

Comparative analysis of Estimated CH4 emissions

1st Scenario: CH4 emission predictions using field CH4 flux data2nd Scenario: CH4 emission predictions using literature CH4 flux values

Conclusions

Indian wetlands emit about 3 Tg methane annually based on emission factors compiled from literature?

Seasonally, summer season fluxes of are CH4 higher as compared to monsoon and winter seasons due tomore favourable conditions of temperature (water and soil), redox potential, water depth, dissolvedoxygen, biological oxygen demand, high plant biomass leading to augmented methanogenic activities insummers.

Seasonally, CH4 emissions for UP are maximum in summer season (54.48 Gg/yr) than monsoon (32.17Gg/yr) and winter season (17.41 Gg/yr) primarily due to the increased temperature which in turn amplifiesthe biological activities to produce and release augmented CH4 emissions.

Comparative analysis of two different scenarios (for UP) has revealed that the total estimated CH4

emissions (Tg/yr) predicted using literature based CH4 flux values indicate 5.10 orders of magnitudes in2010-2011 and 4.12 orders of magnitude during 2011-2012. It indicates that the upscaling of CH4 fluxvalues over large areas using literature CH4 flux values overestimate the CH4 emission results. Researchneeded. Need is to carry out studies in different biogeographical regions including South/South-East Asia.

As wetlands are dynamic ecosystems uncertainties still exists in availability of accurate wetland area,impacts of water quality deterioration and global warming on CH4 emission. Research needed.

References

1. Agarwal, Reshu and Garg, J.K. (2008) “Knowledge based classifier of wetlands from coarse resolution satellite data”International Journal of Geoinformatics, Vol 4, No.3, pp:17-23 September, 2008. ISSN 1686-6576.

2. Agarwal, Reshu and Garg, J. K. (2009). Methane emission modeling from water and waterlogged areas using MODISdata. Current Science, 96(1), 36-40.

3. Agarwal, Reshu and Garg, J. K. (2009). A Hierarchical Model for Estimating Methane Emission from Wetlands usingMODIS data and ARIMA Modeling. Journal of Indian Society of Remote sensing (JISRS) (JISRS), 37, 473-481. Springer.

4. Agrawal, R. and Garg, J.K. (2010). Wetland Surface Temperature Estimation using EOS/MODIS Data. InternationalJournal of Geoinformatics,6(3), 49-56.

5. Bansal, S., Chakraborty, M., Katyal, D. Garg, J.K., 2015.Assessment of methane variability from natural wetlands ofUttar Pradesh, India-Implications for tropical countries. Research Journal of Environmental Sciences 9(3), 101-118.

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