Improving Indonesian peatland C stock estimates using ground penetrating radar (GPR) and electrical resistivity imaging (ERI)

Wednesday, 17 December 2014
Neil Terry1, Xavier Comas2, Lee D Slater1, Matthew Warren3, Randy K Kolka4, Agus Kristijono5, Nana Sudiana5, Dadan Nurjaman5 and Taryono Darusman6, (1)Rutgers University Newark, Earth and Environmental Sciences, Newark, NJ, United States, (2)Florida Atlantic University, Boca Raton, FL, United States, (3)USDA Forest Service, Northern Research Station, Durham, NH, United States, (4)USDA Forest Service, Grand Rapids, MN, United States, (5)Indonesian Agency for Assessment and Application of Technology (BPPT), Jakarta, Indonesia, (6)United States Forest Service affiliate, Putur Foundation, Jakarta, Indonesia
Tropical peatlands sequester an estimated 15% of the carbon pool from peatlands worldwide. Indonesian peatlands account for approximately 65% of all tropical peat, and are believed to be the largest global source of carbon dioxide emissions to the atmosphere from degrading peat. However, there is great uncertainty in these estimates due to insufficient data regarding the thickness of organic peat soils and their carbon content. Meanwhile, Indonesian peatlands are threatened by heightening pressure to drain and develop.

Indirect geophysical methods have garnered interest for their potential to non-invasively estimate peat depth and gas content in boreal peatlands. Drawing from these techniques, we employed ground penetrating radar (GPR) and electrical resistivity imaging (ERI) in tandem with direct methods (core sampling) to evaluate the potential of these methods for tropical peatland mapping at 2 distinct study sites on West Kalimantan (Indonesia). We find that: [1] West Kalimantan peatland thicknesses estimated from GPR and ERI in intermediate/shallow peat can vary substantially over short distances (for example, > 2% over less than 0.02° surface topography gradient), [2] despite having less vertical resolution, ERI is able to better resolve peatland thickness in deep peat, and [3] GPR provides useful data regarding peat matrix attributes (such as the presence of wood layers). These results indicate GPR and ERI could help reduce uncertainty in carbon stocks and aid in responsible land management decisions in Indonesia.