EP042-06
Characterizing Soil Drying Rates in Tropical Peatlands

Friday, 11 December 2020: 11:02
Virtual
Nathan Dadap, Stanford University, Stanford, CA, United States, Alison Hoyt, Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, Cambridge, CA, United States, Alex Cobb, Singapore-MIT Alliance for Research and Technology (SMART), Singapore, Singapore, Charles Franklin Harvey, Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, Cambridge, MA, United States and Alexandra G. Konings, Stanford University, Department of Earth System Science, Stanford, CA, United States
Abstract:
In undisturbed tropical peatlands, waterlogged conditions suppress decomposition rates and prevent fire. However, in recent decades, a majority of peatlands in Southeast Asia has been drained for logging and agricultural use. This has created dry conditions that, during drought years, lead to widespread wildfires. Peat fires release hundreds of megatons of carbon dioxide to the atmosphere and create deadly smoke throughout the region. Although soil moisture determines peat flammability, peatland soil moisture dynamics have not been studied. While detailed hydrologic models can be adapted to tropical peat soils, the data scarcity in this region makes accurate parametrization of such models challenging, particularly across a range of land use types, drainage regimes, and peat properties.

Here, instead, we use remotely sensed soil moisture timeseries across Southeast Asia to study the processes that govern their dynamics. We characterize soil drying rates in Southeast Asian peatlands by parametrizing a one-dimensional hydrologic loss function using remotely sensed observations from the Soil Moisture Active Passive (SMAP) satellite at 9 km resolution from 2015-present. This loss function describes the rate at which soil dries conditioned on the initial soil moisture value across different evapotranspiration and drainage regimes. Periods of dry-down are identified by filtering out observations coincident with rain events, using data from the Climate Hazards Group InfraRed Precipitation with Station dataset (CHIRPS). We then quantify relationships between land use type, drainage, and soil drying rates (characterized based on the fitted loss functions). These analyses represent a first attempt to characterize peatland soil moisture dynamics and to understand how they are impacted by peatland disturbances.