A cost-efficient method to assess carbon stocks in tropical peat soil

Warren, Matthew; Kauffman, J. Boone; Murdiyarso, Daniel; Anshari, Gusti Z.; Hergoualc’h, Kristell; Kurnianto, S.; Purbopuspito, J.; Gusmayanti, Evi; Afifudin, M.; Rahajoe, Joeni Setijo; Alhamd, Laode; Limin, Suwido H.; Anas, Iswandi

doi:10.5194/bg-9-4477-2012

Cited by 67 publications

(30 citation statements)

References 27 publications

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“…where L fire is the quantity of CO 2 or non-CO 2 gas emitted by the fire (tonnes), A is the burned area (5.2 ha), B D is dry bulk density (0.106 g·cm −3 from [35]), DoB is depth of burn (0.23 m), C f is the combustion factor (assumed to be 1, dimensionless), and G ef is the biome specific emission factors for CO 2 -C, CO-C and CH 4 -C (434.7, 109.3 and 5.6 gC·kg −1 dry mass burned respectively, from [3]). …”

Section: Methods For Calculating Emissions Estimatesmentioning

confidence: 99%

“…Peat bulk density was taken as 0.106 ± 0.028 g·cm −3 in Jambi [35], and for emissions factors we used the first field-derived emission factors collected for Indonesian tropical peat fires by [3], assessed during the El Niño-exacerbated fires of 2015. For CO 2 , CH 4 and CO, these EFs are 1594 ± 61, 7.4 ± 2.3, and 255 ± 39 g·kg −1 respectively for peat-only emissions.…”

Section: Methods For Calculating Emissions Estimatesmentioning

confidence: 99%

“…Much of the area is degraded to some extent, with drainage canals and logging trails penetrating deep into the National Park [33]. The whole area is dominated by organosols (over 55% organic matter [34], ranging from 4.1 to 6.4 m deep, which equates to an estimated carbon density of between 2252 and 3228 t·C·ha −1 [35]. Much of the landscape around Berbak National Park has been fire-affected (Figure 2b-d), with fires mostly associated with forest degradation and drainage of the peat for agriculture.…”

Section: Sitesmentioning

confidence: 99%

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Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR

et al. 2016

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Abstract:We provide the first assessment of tropical peatland depth of burn (DoB) using structure from motion (SfM) photogrammetry, applied to imagery collected using a low-cost, low-altitude unmanned aerial vehicle (UAV) system operated over a 5.2 ha tropical peatland in Jambi Province on Sumatra, Indonesia. Tropical peat soils are the result of thousands of years of dead biomass accumulation, and when burned are globally significant net sources of carbon emissions. The El Niño year of 2015 saw huge areas of Indonesia affected by tropical peatland fires, more so than any year since 1997. However, the Depth of Burn (DoB) of these 2015 fires has not been assessed, and indeed has only previously been assessed in few tropical peatland burns in Kalimantan. Therefore, DoB remains arguably the largest uncertainty when undertaking fire emissions calculations in these tropical peatland environments. We apply a SfM photogrammetric methodology to map this DoB metric, and also investigate combustion heterogeneity using orthomosaic photography collected using the UAV system. We supplement this information with pre-burn airborne light detection and ranging (LiDAR) data, reducing uncertainty by estimating pre-burn soil height more accurately than from interpolation of adjacent unburned areas alone. Our pre-and post-fire Digital Terrain Models (DTMs) show accuracies of 0.04 and 0.05 m (root-mean-square error, RMSE) respectively, compared to ground-based global navigation satellite system (GNSS) surveys. Our final DoB map of a 5.2 ha degraded peat swamp forest area neighboring Berbak National Park (Sumatra, Indonesia) shows burn depths extending from close to zero to over 1 m, with a mean (±1σ) DoB of 0.23 ± 0.19 m. This lies well within the range found by the few other studies available (on Kalimantan; none are available on Sumatra). Our combustion heterogeneity analysis suggests the deepest burns, which extend to~1.3 m, occur around tree roots. We use these DoB data within the Intergovernmental Panel on Climate Change (IPCC) default equation for fire emissions to estimate mean carbon emissions as 134 ± 29 t·C·ha −1 for this peatland fire, which is in an area that had not had a recorded fire previously. This is amongst the highest per unit area fuel consumption anywhere in the world for landscape fires. Our approach provides significant uncertainty reductions in such emissions calculations via the reduction in DoB uncertainty, and by using the UAV SfM approach this is accomplished at a fraction of the cost of airborne LiDAR-albeit over limited sized areas at present. Deploying this approach at locations across Indonesia, sampling a variety of fire-affected landscapes, would provide new and important DoB statistics for producing optimized carbon and greenhouse gas (GHG) emissions estimates from peatland fires.

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Section: Methods For Calculating Emissions Estimatesmentioning

confidence: 99%

Section: Methods For Calculating Emissions Estimatesmentioning

confidence: 99%

Section: Sitesmentioning

confidence: 99%

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Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR

et al. 2016

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“…A large amount of carbon emission is produced by peatlands, which is mostly determined by the depth or the thickness of the peat [1,2,8]. Accurate information parameters on the depth and the thickness of the peat must be used in this research.…”

Section: Introductionmentioning

confidence: 99%

“…The study of peat soil has developed rapidly to be able to determine carbon emissions, especially in the peatlands of Indonesia [1][2][3][4][5][6][7]. A large amount of carbon emission is produced by peatlands, which is mostly determined by the depth or the thickness of the peat [1,2,8].…”

Section: Introductionmentioning

confidence: 99%

Identifying Peat Soil Layers in the South Kalimantan, Indonesia Using K-Means Clustering

Iryanti¹,

Aminudin²,

Agustine³

et al. 2018

Preprint

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Various type of soils have been identified based on their electrical and magnetic properties, especially with regards to peat soils. Peat soils are commonly considered as partly decomposed vegetation. In this study, electrical and magnetic properties have been used in K-means clustering to identify layers of peat soils. K-means clustering is a partitioning method that treats observations in the data. Data cores were obtained at every centimeter and examined for their electrical conductivity (σ) and magnetic susceptibility (χm) properties. A 291 cm core was obtained at Tegal Arum Village in South Kalimantan, Indonesia. The K-means clustering results indicate two different layers at 148 cm, and this is supported by loss on ignition (LOI) measurements. In the first layers, a 87.65% LOI was found associated with peat soils (above 248 cm). Whereas, in the second layers, there was a 26.11% LOI associated with mineral soils (below 248 cm). The results of this study using K-means clustering can be used to delineate soil layers.

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In Situ Tropical Peatland Fire Emission Factors and Their Variability, as Determined by Field Measurements in Peninsula Malaysia

Smith

Evers

Yule

et al. 2018

Global Biogeochemical Cycles

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Fires in tropical peatlands account for >25% of estimated total greenhouse gas emissions from deforestation and degradation. Despite significant global and regional impacts, our understanding of specific gaseous fire emission factors (EFs) from tropical peat burning is limited to a handful of studies. Furthermore, there is substantial variability in EFs between sampled fires and/or studies. For example, methane EFs vary by 91% between studies. Here we present new fire EFs for the tropical peatland ecosystem; the first EFs measured for Malaysian peatlands, and only the second comprehensive study of EFs in this crucial environment. During August 2015 (under El Niño conditions) and July 2016, we embarked on field campaigns to measure gaseous emissions at multiple peatland fires burning on deforested land in Southeast Pahang (2015) and oil palm plantations in North Selangor (2016), Peninsula Malaysia. Gaseous emissions were measured using open‐path Fourier transform infrared spectroscopy. The IR spectra were used to retrieve mole fractions of 12 different gases present within the smoke (including carbon dioxide and methane), and these measurements used to calculate EFs. Peat samples were taken at each burn site for physicochemical analysis and to explore possible relationships between specific physicochemical properties and fire EFs. Here we present the first evidence to indicate that substrate bulk density affects methane fire EFs reported here. This novel explanation of interplume, within‐biome variability, should be considered by those undertaking greenhouse gas accounting and haze forecasting in this region and is of importance to peatland management, particularly with respect to artificial compaction.

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A cost-efficient method to assess carbon stocks in tropical peat soil

Cited by 67 publications

References 27 publications

Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR

Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR

Identifying Peat Soil Layers in the South Kalimantan, Indonesia Using K-Means Clustering

In Situ Tropical Peatland Fire Emission Factors and Their Variability, as Determined by Field Measurements in Peninsula Malaysia

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