Modelling heat, water and carbon fluxes in mown grassland under multi-objective and multi-criteria constraints
2016 (English)In: Environmental Modelling & Software, ISSN 1364-8152, E-ISSN 1873-6726, Vol. 80, 201-224 p.Article in journal (Refereed) PublishedText
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.
Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 80, 201-224 p.
Model performance, Modelling heat, water, carbon flux, Multi-objective and multi-criteria constraints, Parameter uncertainty
IdentifiersURN: urn:nbn:se:kth:diva-186961DOI: 10.1016/j.envsoft.2016.02.025ISI: 000376218300017ScopusID: 2-s2.0-84960108455OAI: oai:DiVA.org:kth-186961DiVA: diva2:930514
QC 201605242016-05-242016-05-162016-06-13Bibliographically approved