Modelling heat, water and carbon fluxes in mown grassland under multi-objective and multi-criteria constraints

Nimai Senapati; Per-Erik Jansson; Pete Smith; Abad Chabbi

doi:10.1016/j.envsoft.2016.02.025

Modelling heat, water and carbon fluxes in mown grassland under multi-objective and multi-criteria constraints

Nimai Senapati^*, Per-Erik Jansson, Pete Smith, Abad Chabbi

^*Corresponding author for this work

Aberdeen Centre For Environmental Sustainability

Research output: Contribution to journal › Article › peer-review

19 Citations (Scopus)

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	https://doi.org/10.1016/j.envsoft.2016.02.025
Publication status	Published - Jun 2016

Bibliographical note

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.

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.envsoft.2016.02.025Licence: Unspecified

Cite this

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title = "Modelling heat, water and carbon fluxes in mown grassland under multi-objective and multi-criteria constraints",

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.",

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",

author = "Nimai Senapati and Per-Erik Jansson and Pete Smith and Abad Chabbi",

note = "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-{\'e}cosyst{\`e}mes, Cycles Biog{\'e}ochimique et Biodiversit{\'e}” (ANR-11-INBS-0001) (SOERE-ACBB http://www.soere-acbb.com/fr/), Allenvi and ICOS France. We are grateful to Christophe de-Berranger, C{\'e}dric 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.",

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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.

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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

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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

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DO - 10.1016/j.envsoft.2016.02.025

M3 - Article

SN - 1364-8152

VL - 80

SP - 201

EP - 224

JO - Environmental Modelling and Software

JF - Environmental Modelling and Software

ER -

Modelling heat, water and carbon fluxes in mown grassland under multi-objective and multi-criteria constraints

Abstract

Bibliographical note

Keywords

UN SDGs

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