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Drainage Canals in Southeast Asian Peatlands Increase Carbon Emissions
  • +6
  • Nathan C Dadap,
  • Alison M Hoyt,
  • Alexander R Cobb,
  • Doruk Oner,
  • Mateusz Kozinski,
  • Pascal V Fua,
  • Krishna Rao,
  • Charles F Harvey,
  • Alexandra G Konings
Nathan C Dadap
Stanford University

Corresponding Author:ndadap@stanford.edu

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Alison M Hoyt
Lawrence Berkeley National Laboratory
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Alexander R Cobb
Singapore-MIT Alliance for Research and Technology
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Doruk Oner
École Polytechnique Fédérale de Lausanne
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Mateusz Kozinski
École Polytechnique Fédérale de Lausanne
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Pascal V Fua
École Polytechnique Fédérale de Lausanne
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Krishna Rao
Stanford University
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Charles F Harvey
Massachusetts Institute of Technology
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Alexandra G Konings
Stanford University
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Abstract

Drainage canals associated with logging and agriculture dry out organic soils in tropical peatlands, thereby threatening the viability of long-term carbon stores due to increased emissions from decomposition, fire, and fluvial transport. In Southeast Asian peatlands, which have experienced decades of land use change, the exact extent and spatial distribution of drainage canals are unknown. This has prevented regional-scale investigation of the relationships between drainage, land use, and carbon emissions. Here, we create the first regional map of drainage canals using high resolution satellite imagery and a convolutional neural network. We find that drainage is widespread-occurring in at least 65% of peatlands and across all land use types. Although previous estimates of peatland carbon emissions have relied on land use as a proxy for drainage, our maps show substantial variation in drainage density within land use types. Subsidence rates, and corresponding carbon losses from decomposition, are 3.2 times larger in intensively drained areas than in non-drained areas, highlighting the central role of drainage in mediating peat carbon fluxes. Accounting for drainage canals was found to improve a subsidence prediction model by 30%, suggesting that canals contain information about subsidence not captured by land use alone. Thus, our dataset can be used to improve carbon emissions predictions in peatlands and to target areas for hydrologic restoration.