Tropical Peatland Hydrology Simulated With a Global Land Surface Model. (28th February 2022)

• Record Type: Journal Article
• Authors: Apers, S.; De Lannoy, G. J. M.; Baird, A. J.; Cobb, A. R.; Dargie, G. C.; del Aguila Pasquel, J.; Gruber, A.; Hastie, A.; Hidayat, H.; Hirano, T.; Hoyt, A. M.; Jovani‐Sancho, A. J.; Katimon, A.; Kurnain, A.; Koster, R. D.; Lampela, M.; Mahanama, S. P. P.; Melling, L.; Page, S. E.; Reichle, R. H.; Taufik, M.; Vanderborght, J.; Bechtold, M.
• Is Part Of: Journal of advances in modeling earth systems. Volume 14:Number 3(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-28
• Subjects: PEATCLSM -- groundwater -- drainage -- peat swamp -- evaporation -- wetland; Geological modeling -- Periodicals; Climatology -- Periodicals; Geochemical modeling -- Periodicals; 551.5011
• DOI: 10.1029/2021MS002784
• Languages: English
• ISSNs: 1942-2466

Abstract

Abstract: Tropical peatlands are among the most carbon‐dense ecosystems on Earth, and their water storage dynamics strongly control these carbon stocks. The hydrological functioning of tropical peatlands differs from that of northern peatlands, which has not yet been accounted for in global land surface models (LSMs). Here, we integrated tropical peat‐specific hydrology modules into a global LSM for the first time, by utilizing the peatland‐specific model structure adaptation (PEATCLSM) of the NASA Catchment Land Surface Model (CLSM). We developed literature‐based parameter sets for natural (PEATCLSMTrop, Nat ) and drained (PEATCLSMTrop, Drain ) tropical peatlands. Simulations with PEATCLSMTrop, Nat were compared against those with the default CLSM version and the northern version of PEATCLSM (PEATCLSMNorth, Nat ) with tropical vegetation input. All simulations were forced with global meteorological reanalysis input data for the major tropical peatland regions in Central and South America, the Congo Basin, and Southeast Asia. The evaluation against a unique and extensive data set of in situ water level and eddy covariance‐derived evapotranspiration showed an overall improvement in bias and correlation compared to the default CLSM version. Over Southeast Asia, an additional simulation with PEATCLSMTrop, Drain was run to address the large fraction of drained tropical peatlands in this region. PEATCLSMTrop, Drain outperformed CLSM, PEATCLSMNorth, Nat, and PEATCLSMTrop, Nat over drained sites. Despite the overall improvements of PEATCLSMTrop, Nat over CLSM, there are strong differences in performance between the three study regions. We attribute these performance differences to regional differences in accuracy of meteorological forcing data, and differences in peatland hydrologic response that are not yet captured by our model. Plain Language Summary: Tropical peatlands are wetlands in which plant material accumulates under waterlogged conditions and develops into a dense organic soil layer. Disturbance of their self‐regulating hydrology by external factors such as artificial drainage, land use change, and climate change can quickly convert these immense carbon stocks into strong sources of greenhouse gases. Including the hydrology of tropical peatlands into global Earth system models allows us to understand the impact of such external disturbances. We developed the first hydrology modules for natural and drained tropical peatlands to plug into the NASA Goddard Earth Observing System modeling framework. Our results display strong regional differences, and indicate that the accuracy of our model is limited by rainfall data quality and by our understanding of how peatland hydrology differs across the three regions that contain the major tropical peatland areas (Central and South America, the Congo Basin, and Southeast Asia). Nonetheless, simulations with both of our modules correlate better than the default model to field observations of water level and evapotranspiration over all three regions. Key Points: For the first time, a global land surface model was adapted to include natural and drained tropical peatland hydrology Evaluation with in situ data shows that the tropical natural and drained peatland model versions both outperform the default model version Regional skill differences are attributed to accuracy differences of model parameterization and meteorological forcing data across regions