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 (R-2 = 0.61, ME = 0.48 MJ m(-2) day(-1)), soil water contents (R-2 = 0.68, ME = 0.34%) and carbon-dioxide flux (R-2 = 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. (C) 2016 Elsevier Ltd. All rights reserved.
| Original language | English |
|---|---|
| Pages (from-to) | 201-224 |
| Number of pages | 24 |
| Journal | Environmental Modelling and Software |
| Volume | 80 |
| Early online date | 22 Mar 2016 |
| DOIs | |
| Publication status | Published - Jun 2016 |
Keywords
- Modelling heat, water, carbon flux
- Multi-objective and multi-criteria constraints
- Model performance
- Parameter uncertainty
- Pasture simulation-model
- Scots Pine ecosystem
- Soil carbon
- Terrestrial carbon
- Porous-media
- NET carbon
- Bare soil
- Uncertainty
- Calibration
- Temperature
Cite this
Modelling heat, water and carbon fluxes in mown grassland under multi-objective and multi-criteria constraints. / Senapati, Nimai; Jansson, Per-Erik; Smith, Pete; Chabbi, Abad.
In: Environmental Modelling and Software, Vol. 80, 06.2016, p. 201-224.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Modelling heat, water and carbon fluxes in mown grassland under multi-objective and multi-criteria constraints
AU - Senapati, Nimai
AU - Jansson, Per-Erik
AU - Smith, Pete
AU - Chabbi, Abad
N1 - Acknowledgements This work was supported financially by the European community's Seventh Framework Programme (FP2007-2013) under grant agreement n° 262060 (ExpeER). The research leading to these results has received funding principally from the National Research Infrastructure “Agro-écosystèmes, Cycles Biogéochimique et Biodiversité” (ANR-11-INBS-0001) (SOERE-ACBB http://www.soere-acbb.com/fr/), Allenvi and ICOS France. We are grateful to Christophe de-Berranger, Cédric Perrot and Xavier Charrier for technical and field work assistance. We thank the anonymous Reviewers and Associate Editor for their valuable comments and suggestions that help us to improve the manuscript.
PY - 2016/6
Y1 - 2016/6
N2 - 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 (R-2 = 0.61, ME = 0.48 MJ m(-2) day(-1)), soil water contents (R-2 = 0.68, ME = 0.34%) and carbon-dioxide flux (R-2 = 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. (C) 2016 Elsevier Ltd. All rights reserved.
AB - 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 (R-2 = 0.61, ME = 0.48 MJ m(-2) day(-1)), soil water contents (R-2 = 0.68, ME = 0.34%) and carbon-dioxide flux (R-2 = 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. (C) 2016 Elsevier Ltd. All rights reserved.
KW - Modelling heat, water, carbon flux
KW - Multi-objective and multi-criteria constraints
KW - Model performance
KW - Parameter uncertainty
KW - Pasture simulation-model
KW - Scots Pine ecosystem
KW - Soil carbon
KW - Terrestrial carbon
KW - Porous-media
KW - NET carbon
KW - Bare soil
KW - Uncertainty
KW - Calibration
KW - Temperature
U2 - 10.1016/j.envsoft.2016.02.025
DO - 10.1016/j.envsoft.2016.02.025
M3 - Article
VL - 80
SP - 201
EP - 224
JO - Environmental Modelling and Software
JF - Environmental Modelling and Software
SN - 1364-8152
ER -