Drainage Canals in Southeast Asian Peatlands Increase Carbon Emissions

Dadap, Nathan; Hoyt, Alison M.; Cobb, Ale×ander R.; Öner, Doruk; Koziński, Mateusz; Fua, Pascal; Rao, K. H.; Harvey, Charles F.; Konings, Alexandra G.

doi:10.1002/essoar.10505767.1

Cited by 3 publications

(7 citation statements)

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“…Although the degree of artificial drainage varies spatially and in time, we approximated the effects of drainage using a single set of representative parameters, similar to how vegetation with different surface energy exchange characteristics is combined in a single LSM land cover type. The discharge function of PEATCLSM Trop,Drain (see Section 2.2.4, and Figure 6b) was developed using information on drainage canals in Southeast Asian peatlands (Dadap et al., 2021). This map of drainage canals could be used to develop a spatially varying discharge function for PEATCLSM Trop,Drain , but also to spatially distinguish between natural and drained peatlands using a threshold.…”

Section: Discussionmentioning

confidence: 99%

“…However, the map only represents current drainage canals and doesn't take local canal management into account. Although land use has been mapped over time (Miettinen et al., 2016), drainage is not always well‐coordinated with it (Dadap et al., 2021), making the drainage map's usefulness for long simulation periods uncertain.…”

Section: Discussionmentioning

confidence: 99%

“…The median parameter value for L ditch (= 0.0318 m m −2 ) was based on Dadap et al. (2021), and the mean w strip (= 31.4 m) was based on its inverse relationship to L ditch . The mean z ditch (= −0.68 m) was obtained from measurements in acacia, rubber and oil palm plantations, and intensively logged forests (Biancalani & Avagyan, 2014; Carlson et al., 2015; Evans et al., 2019; Hooijer et al., 2006; Ritzema et al., 1998; Wösten et al., 2008).…”

Section: Methodsmentioning

confidence: 99%

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Tropical Peatland Hydrology Simulated With a Global Land Surface Model

Apers

Lannoy

Baird

et al. 2022

J Adv Model Earth Syst

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Tropical peatlands are among the most carbon-dense ecosystems on Earth, and their water storage dynamics strongly control these carbon stocks. The hydrological functioning of tropical peatlands differs from that of northern peatlands, which has not yet been accounted for in global land surface models (LSMs). Here, we integrated tropical peat-specific hydrology modules into a global LSM for the first time, by utilizing the peatland-specific model structure adaptation (PEATCLSM) of the NASA Catchment Land Surface Model (CLSM). We developed literature-based parameter sets for natural (PEATCLSM Trop,Nat ) and drained (PEATCLSM Trop,Drain ) tropical peatlands. Simulations with PEATCLSM Trop,Nat were compared against those with the default CLSM version and the northern version of PEATCLSM (PEATCLSM North,Nat ) with tropical vegetation input. All simulations were forced with global meteorological reanalysis input data for the major tropical peatland regions in Central and South America, the Congo Basin, and Southeast Asia. The evaluation against a unique and extensive data set of in situ water level and eddy covariance-derived evapotranspiration showed an overall improvement in bias and correlation compared to the default CLSM version. Over Southeast Asia, an additional simulation with PEATCLSM Trop,Drain was run to address the large fraction of drained tropical peatlands in this region. PEATCLSM Trop,Drain outperformed CLSM, PEATCLSM North,Nat , and PEATCLSM Trop,Nat over drained sites. Despite the overall improvements of PEATCLSM Trop,Nat over CLSM, there are strong differences in performance between the three study regions. We attribute these performance differences to regional differences in accuracy of meteorological forcing data, and differences in peatland hydrologic response that are not yet captured by our model. Plain Language SummaryTropical peatlands are wetlands in which plant material accumulates under waterlogged conditions and develops into a dense organic soil layer. Disturbance of their selfregulating hydrology by external factors such as artificial drainage, land use change, and climate change can quickly convert these immense carbon stocks into strong sources of greenhouse gases. Including the hydrology of tropical peatlands into global Earth system models allows us to understand the impact of such external disturbances. We developed the first hydrology modules for natural and drained tropical peatlands to plug into the NASA Goddard Earth Observing System modeling framework. Our results display strong regional differences, and indicate that the accuracy of our model is limited by rainfall data quality and by our understanding of how peatland hydrology differs across the three regions that contain the major tropical peatland areas (Central and South America, the Congo Basin, and Southeast Asia). Nonetheless, simulations

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Tropical Peatland Hydrology Simulated With a Global Land Surface Model

Apers

Lannoy

Baird

et al. 2022

J Adv Model Earth Syst

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“…In combination with the latest measurements of surface water extent from NISAR (also to launch in 2022), and height measurements from modern laser and radar altimeters (e.g., ICESat‐2, Sentinel 6 Michael Freilich), the availability of data for surface water studies is rapidly expanding, leading to major breakthroughs (Cooley et al., 2021). The influx of commercial imagery from companies such as Maxar and Planet is also changing this field rapidly by enabling frequent (∼daily), fine spatial (≤3 m) observations of surface water extent (Cooley et al., 2017, 2019; Dadap et al., 2021), especially in smaller lakes and rivers. The combination of the first dedicated surface water mission (SWOT), widely available fine‐resolution optical (SmallSats, Sentinel‐2), and radar (NISAR) imagery, and additional spaceborne altimeters (Sentinel 6 Michael Freilich, ICESat‐2) mean that a “golden age” of surface water remote sensing is clearly on the horizon.…”

Section: Progress In Hydrologic Remote Sensingmentioning

confidence: 99%

Achieving Breakthroughs in Global Hydrologic Science by Unlocking the Power of Multisensor, Multidisciplinary Earth Observations

et al. 2021

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Over the last half century, remote sensing has transformed hydrologic science. Whereas early efforts were devoted to observation of discrete variables, we now consider spaceborne missions dedicated to interlinked global hydrologic processes. Furthermore, cloud computing and computational techniques are accelerating analyses of these data. How will the hydrologic community use these new resources to better understand the world's water and related challenges facing society? In this commentary, we suggest that optimizing the benefits of remote sensing for advancing hydrologic research will happen by integrating multidisciplinary and multisensor data, leveraging commercial satellite measurements, and employing data assimilation, cloud computing, and machine learning. We provide several recommendations to these ends.

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“…In addition, the draining of peatlands for oil palm, acacia, and rice plantations amplifies these carbon cycle feedbacks through the drying and burning of carbon rich peat. Southeast (SE) Asian peatlands store globally significant amounts of carbon, 69 GtC, which accounts for 65 % of global tropical peat deposits, and are especially at risk due to drainage 1,5,6 . Carbon released from these peatlands poses a serious feedback on anthropogenic climate change.…”

Section: Introductionmentioning

confidence: 99%

Southeast Asian peatland drainage emits 220 Mt of carbon per year, equivalent to 2.2% of global fossil-fuel emissions

Larson

Dadap

Longo

et al. 2022

Preprint

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Southeast Asian peatlands are climatically important ecosystems, storing approximately 70 billion tons of carbon. Natural and human-induced droughts are lowering peatland water tables, increasing decomposition and the risk of peat-burning wildfires. The rapid nature of carbon losses arising from peatland drainage and accompanying fire-related losses compared to the slow accumulation of peat means that the effects of peatland drainage are essentially irreversible on human timescales. Here, we use a terrestrial biosphere model incorporating vertically-resolved peatland carbon and water dynamics to predict decomposition and fire in Southeast Asia as a result drainage-induced drying. The model captures observed patterns of interannual and seasonal variation in soil moisture and its soil moisture estimates are a better predictor of observed burned area fraction than either precipitation or remotely-sensed estimates of surface soil moisture (r2=0.63, 0.50, 0.56 respectively). Simulations of a fully-drained 1.4 m peat deposit emit an additional 9 tC ha-1 yr-1 and 13 tC ha-1 yr-1 from decomposition and fire respectively. The emissions from decomposition are linearly related to the depth of drainage and can reach up to 31 tC ha-1 yr-1 when fully drained. At regional scales, these estimates imply that 220 MtC yr-1, or 2.2% of global fossil fuel emissions, are being emitted from Indonesian and Malaysian peatlands due to drainage. The vulnerability of these large, concentrated carbon stocks, combined with their long timescale of accumulation, underscore the importance for preserving tropical peatlands to avoid further exacerbation of human induced climate change.

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Drainage Canals in Southeast Asian Peatlands Increase Carbon Emissions

Cited by 3 publications

References 66 publications

Tropical Peatland Hydrology Simulated With a Global Land Surface Model

Tropical Peatland Hydrology Simulated With a Global Land Surface Model

Achieving Breakthroughs in Global Hydrologic Science by Unlocking the Power of Multisensor, Multidisciplinary Earth Observations

Southeast Asian peatland drainage emits 220 Mt of carbon per year, equivalent to 2.2% of global fossil-fuel emissions

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