H194-0006
Extending the PEATCLSM Framework to Tropical Peatlands: Model Evaluation for the Major Tropical Peatland Areas
Wednesday, 16 December 2020
Poster
Sebastian Apers1, Michel Bechtold1,2, Andrew J Baird3, Alex Cobb4, Greta Christina Dargie3, Hidayat Hidayat5,6, Takashi Hirano7, Alison Hoyt8, Yoshiyukii Ishii9, Ayob Katimon10, Randal D Koster11, Maija Lampela12, Sarith P P Mahanama11,13, Lulie Melling14, Susan Elizabeth Page15, Rolf H Reichle11, Hidenori Takahashi16, Mohammed Taufik17, Jan Vanderborght18 and Gabrielle J.M. De Lannoy1, (1)KU Leuven, Department of Earth and Environmental Sciences, Heverlee, Belgium, (2)KU Leuven, Department of Computer Science, Heverlee, Belgium, (3)University of Leeds, School of Geography, Leeds, United Kingdom, (4)Singapore-MIT Alliance for Research and Technology (SMART), Singapore, Singapore, (5)Centre for Limnology, Indonesian Institute of Sciences, Cibinong, Indonesia, (6)Wageningen University, Hydrology and Quantitative Water Management Group, Wageningen, Netherlands, (7)Hokkaido University, Research Faculty of Agriculture, Sapporo, Japan, (8)Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, Cambridge, CA, United States, (9)Hokkaido University, Institute of Low Temperature Science, Saporro, Japan, (10)Universiti Malaysia Perlis, School of Bioprocess Engineering, Arau, Malaysia, (11)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (12)University of Helsinki, Department of Forest Science, Helsinki, Finland, (13)Science Systems and Applications, Inc., Lanham, MD, United States, (14)Sarawak Tropical Peat Research Laboratory Unit, Chief Minister's Department, Kuching, Sarawak, Malaysia, (15)University of Leicester, Department of Geography, Leicester, United Kingdom, (16)Hokkaido University, Hokkaido Institute of Hydro-climate, Saporro, Japan, (17)Bogor Agricultural University (IPB), Department of Geophysics and Meteorology, Bogor, Indonesia, (18)Forschungszentrum Jülich GmbH, Agrosphere (IBG-3), Institute of Bio- and Geosciences, Jülich, Germany
Abstract:
Tropical peatlands have specific water storage dynamics that exert a first-order control on their internal processes and functioning, and distinguish them from surrounding mineral landscapes and northern peatlands. The integration of tropical peat-specific hydrology in an existing global-scale land surface model (LSM) will help our understanding of the peatland sensitivity to external disturbances.
Here, we present the first-ever global-scale LSM specifically adapted for tropical peatland hydrology. Earlier, a module for natural northern peatland processes (PEATCLSMN,Natural) was embedded within the NASA Goddard Earth Observing System (GEOS) Catchment land surface model (CLSM) by Bechtold et al. (2019). We developed a literature-based parameter set for natural (PEATCLSMT,Natural) and drained (PEATCLSMT,Drained) tropical peatlands. As an additional feature, the PEATCLSMT,Natural scheme includes a plant oxygen-stress function to resolve reduced transpiration at high groundwater tables. The basic CLSM structure and the same global input data were used in all PEATCLSM versions to allow future use in operational GEOS products. A suite of simulations with PEATCLSMT,Natural, PEATCLSMN,Natural, and the operational CLSM version (CLSMO, which includes peat as a soil class) was conducted over the Amazon Basin, the Congo Basin and Indonesia. A PEATCLSMT,Drained simulation was added to the Indonesian suite to include the large fraction of drained tropical peatland areas. A preliminary evaluation with in-situ observations of groundwater table depth (WTD) and evapotranspiration (ET) shows overall improvements for simulations with PEATCLSMT,Natural compared to those with the PEATCLSMN,Natural and CLSMO versions for each region. Despite these improvements, strong regional differences occur. The PEATCLSMT,Natural average WTD bias for 9 sites in the Congo Basin is around -0.21 m, compared to -0.02 m for 20 natural sites in Indonesia. When evaluating at 42 drained sites in Indonesia, the average WTD bias is -0.27 m for CLSMO and 0.56 m for PEATCLSMN,Natural, and improves to 0.03 m for PEATCLSMT,Drained. It is expected that regional parameter tuning could further improve the results over the Congo Basin, but this is not common for operational global LSMs. An evaluation over the Amazon Basin is still ongoing.
