Modelling heat,water and carbon fluxes in mown grassland under multi-objective and multi-criteria constraints |
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| Affiliation: | 1. French National Institute for Agricultural Research (INRA), Centre de Recherche Poitou-Charentes, URP3F, Le Chêne – RD150, BP 80006, 86600 Lusignan, France;2. UMR ECOSYS, Centre INRA, Versailles-Grignon, Bâtiment EGER, 78850 Thiverval-Grignon, France;3. Department of Land and Water Resources Engineering, Royal Institute of Technology, Stockholm, Sweden;4. Institute of Biological and Environmental Sciences, University of Aberdeen, 23 St Machar Drive, Aberdeen AB24 3UU, UK;1. Department of Systems and Computer Engineering, Centre for Visualization and Simulation (V-Sim) Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S5B6, Canada;2. Computer Science Department, Universidad de Buenos Aires, Pabellón I, Ciudad Universitaria, 1428 Buenos Aires, Argentina;1. State Key Laboratory of Loess and Quaternary, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an 710075, PR China;2. School of Human Settlement and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, PR China;3. State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, Shaanxi, PR China;4. Administrative Office of Yunwu Mountain in Guyuan, Ningxia, Guyuan 756000, PR China;1. Univ Grenoble Alpes F-38000 Grenoble, France, CEA, LETI, MINATEC Campus, F-38054 Grenoble, France;2. Laboratoire Charles Fabry, Institut d’Optique, CNRS, Univ Paris Sud, 2, Avenue Augustin Fresnel, 91127 Palaiseau cedex, France;1. Centre for Environmental and Climate Research, Lund University, Sölvegatan 37, SE-223 62 Lund, Sweden;2. Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, SE-223 62 Lund, Sweden;3. INRA – UR 1138 Biogéochimie des Ecosystèmes Forestiers, route d’amance, 54280 Champenoux, France |
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| Abstract: | A Monte Carlo-based calibration and uncertainty assessment was performed for heat, water and carbon (C) fluxes, simulated by a soil-plant-atmosphere system model (CoupModel), in mown grassland. Impact of different multi-objective and multi-criteria constraints was investigated on model performance and parameter behaviour. Good agreements between hourly modelled and measurement data were obtained for latent and sensible heat fluxes (R2 = 0.61, ME = 0.48 MJ m?2 day?1), soil water contents (R2 = 0.68, ME = 0.34%) and carbon-dioxide flux (R2 = 0.60, ME = ?0.18 g C m?2 day?1). Multi-objective and multi-criteria constraints were efficient in parameter conditioning, reducing simulation uncertainty and identifying critical parameters. Enforcing multi-constraints separately on heat, water and C processes resulted in the highest model improvement for that specific process, including some improvement too for other processes. Imposing multi-constraints on all groups of variables, associated with heat, water and C fluxes together, resulted in general effective parameters conditioning and model improvement. |
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| Keywords: | Modelling heat water carbon flux Multi-objective and multi-criteria constraints Model performance Parameter uncertainty |
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