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Tropical Peatland Hydrology Simulated With a Global Land Surface Model.
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.
Affiliation
  • Apers S; Department of Earth and Environmental Sciences KU Leuven Heverlee Belgium.
  • De Lannoy GJM; Department of Earth and Environmental Sciences KU Leuven Heverlee Belgium.
  • Baird AJ; School of Geography University of Leeds Leeds UK.
  • Cobb AR; Center for Environmental Sensing and Modeling Singapore-MIT Alliance for Research and Technology Singapore Singapore.
  • Dargie GC; School of Geography University of Leeds Leeds UK.
  • Del Aguila Pasquel J; Instituto de Investigaciones de la Amazonia Peruana (IIAP) Iquitos Peru.
  • Gruber A; Universidad Nacional de la Amazonia Peruana (UNAP) Iquitos Peru.
  • Hastie A; Department of Earth and Environmental Sciences KU Leuven Heverlee Belgium.
  • Hidayat H; School of GeoSciences University of Edinburgh Edinburgh UK.
  • Hirano T; Research Center for Limnology National Research and Innovation Agency Cibinong Indonesia.
  • Hoyt AM; Research Faculty of Agriculture Hokkaido University Sapporo Japan.
  • Jovani-Sancho AJ; Department of Earth System Science Stanford University Stanford CA USA.
  • Katimon A; UK Centre for Ecology and Hydrology Bangor UK.
  • Kurnain A; School of Biosciences University of Nottingham Loughborough UK.
  • Koster RD; Faculty of Chemical Engineering Technology Universiti Malaysia Perlis Kangar Malaysia.
  • Lampela M; Department of Soil Science Lambung Mangkurat University Banjarmasin Indonesia.
  • Mahanama SPP; Global Modeling and Assimilation Office NASA Goddard Space Flight Center Greenbelt MD USA.
  • Melling L; Department of Forest Sciences University of Helsinki Helsinki Finland.
  • Page SE; Global Modeling and Assimilation Office NASA Goddard Space Flight Center Greenbelt MD USA.
  • Reichle RH; Science Systems and Applications Inc. Lanham MD USA.
  • Taufik M; Sarawak Tropical Peat Research Institute Kuching Malaysia.
  • Vanderborght J; School of Geography, Geology and the Environment University of Leicester Leicester UK.
  • Bechtold M; Global Modeling and Assimilation Office NASA Goddard Space Flight Center Greenbelt MD USA.
J Adv Model Earth Syst ; 14(3): e2021MS002784, 2022 Mar.
Article in En | MEDLINE | ID: mdl-35860446
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Adv Model Earth Syst Year: 2022 Document type: Article Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Adv Model Earth Syst Year: 2022 Document type: Article Country of publication: United States