High Resolution Mapping of Peatland Hydroperiod at a High-Latitude Swedish Mire

Nathan Torbick,Changsheng Li,Andreas Persson,Patrick Crill,Stephen Hagen,Steve Frolking,David Olefeldt,William Salas

doi:10.3390/rs4071974

Abstract

Monitoring high latitude wetlands is required to understand feedbacks between terrestrial carbon pools and climate change. Hydrological variability is a key factor driving biogeochemical processes in these ecosystems and effective assessment tools are critical for accurate characterization of surface hydrology, soil moisture, and water table fluctuations. Operational satellite platforms provide opportunities to systematically monitor hydrological variability in high latitude wetlands. The objective of this research application was to integrate high temporal frequency Synthetic Aperture Radar (SAR) and high spatial resolution Light Detection and Ranging (LiDAR) observations to assess hydroperiod at a mire in northern Sweden. Geostatistical and polarimetric (PLR) techniques were applied to determine spatial structure of the wetland and imagery at respective scales (0.5 m to 25 m). Variogram, spatial regression, and decomposition approaches characterized the sensitivity of the two platforms (SAR and LiDAR) to wetland hydrogeomorphology, scattering mechanisms, and data interrelationships. A Classification and Regression Tree (CART), based on random forest, fused multi-mode (fine-beam single, dual, quad pol) Phased Array L-band Synthetic Aperture Radar (PALSAR) and LiDAR-derived elevation to effectively map hydroperiod attributes at the Swedish mire across an aggregated warm season (May–September, 2006–2010). Image derived estimates of water and peat moisture were sensitive (R2 = 0.86) to field measurements of water table depth (cm). Peat areas that are underlain by permafrost were observed as areas with fluctuating soil moisture and water table changes.

Highlights

Trends in climate change and permafrost degradation in northern high latitudes have raised questions over the potential greenhouse gas emissions response from permafrost, lakes, and wetlands.Northern high latitude soils contain approximately 1,000 petagrams (Pg) of carbon in the top 3 m [1].Changing climate is likely to increase vulnerability of this soil carbon [2], and could alter net CO2 and CH4 emissions significantly [3,4,5]
The Classification and Regression Tree (CART) was useful for ingesting different data modes and scales to seamlessly generate metrics sensitive to key wetland hydroperiod attributes
The L-band data was found to be quantitatively sensitive to water table depth and qualitatively sensitive to soil moisture as measured at the mire

Summary

Introduction

Trends in climate change and permafrost degradation in northern high latitudes have raised questions over the potential greenhouse gas emissions response from permafrost, lakes, and wetlands.Northern high latitude soils contain approximately 1,000 petagrams (Pg) of carbon in the top 3 m [1].Changing climate is likely to increase vulnerability of this soil carbon [2], and could alter net CO2 and CH4 emissions significantly [3,4,5]. Trends in climate change and permafrost degradation in northern high latitudes have raised questions over the potential greenhouse gas emissions response from permafrost, lakes, and wetlands. Northern high latitude soils contain approximately 1,000 petagrams (Pg) of carbon in the top 3 m [1]. Changing climate is likely to increase vulnerability of this soil carbon [2], and could alter net CO2 and CH4 emissions significantly [3,4,5]. One of the primary drivers of net emissions in peatlands response is hydrological flux and water balance, which can influence both rates of methane and carbon dioxide emissions and of permafrost thaw [6,7]. Accurate spatiotemporal information on hydrological variability is critical for assessing peatland emissions response to climate change.

Methods

Results

Conclusion