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A global Bayesian sensitivity analysis of the 1d SimSphere soil-vegetation-atmospheric transfer (SVAT) model using Gaussian model emulation

Petropoulos, G.; Wooster, M. J.; Carlson, T. N.; Kennedy, M. C. and Scholze, M. LU (2009) In Ecological Modelling 220(19). p.2427-2440
Abstract

Sensitivity analysis consists of an integral and important validatory check of a computer simulation model before the code is used in performing any kind of analysis operation. The present paper demonstrates the use of a relatively new method and tool for conducting global sensitivity analysis (GSA) for environmental models, providing simultaneously the first GSA study of the widely used 1d soil-vegetation-atmospheric transfer (SVAT) model named SimSphere. A software platform called the Gaussian emulation machine for sensitivity analysis (GEM SA), which has been developed for performing a GSA via Bayesian theory, is applied to SimSphere model in order to identify the most responsive model inputs to the simulation of key model outputs,... (More)

Sensitivity analysis consists of an integral and important validatory check of a computer simulation model before the code is used in performing any kind of analysis operation. The present paper demonstrates the use of a relatively new method and tool for conducting global sensitivity analysis (GSA) for environmental models, providing simultaneously the first GSA study of the widely used 1d soil-vegetation-atmospheric transfer (SVAT) model named SimSphere. A software platform called the Gaussian emulation machine for sensitivity analysis (GEM SA), which has been developed for performing a GSA via Bayesian theory, is applied to SimSphere model in order to identify the most responsive model inputs to the simulation of key model outputs, detect their interactions and derive absolute sensitivity measures concerning the model structure. This study is also very timely in that, use of this particular SVAT model is currently being considered to be used in a scheme being developed for the operational retrieval of the soil surface moisture content by National Polar-orbiting Operational Environmental Satellite System (NPOESS), in a series of satellite platforms that are due to be launched in the next 12 years starting from 2016. The employed GSA method was found capable of identifying the most responsive SimSphere inputs and also of capturing their key interactions for each of the simulated target quantities on which the GSA was conducted. The most sensitive model inputs were the topography parameters (slope, aspect) as well as the fractional vegetation cover and soil surface moisture availability. The implications of these findings for the future use of SimSphere are discussed.

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author
publishing date
type
Contribution to journal
publication status
published
subject
keywords
BACCO GEM SA, Gaussian process emulator, Sensitivity analysis, SimSphere, SVAT model
in
Ecological Modelling
volume
220
issue
19
pages
14 pages
publisher
Elsevier
external identifiers
  • scopus:69049120551
ISSN
0304-3800
DOI
10.1016/j.ecolmodel.2009.06.006
language
English
LU publication?
no
id
c2cea834-e795-4551-b628-6161a29fcaba
date added to LUP
2019-03-14 21:22:13
date last changed
2019-09-15 05:15:01
@article{c2cea834-e795-4551-b628-6161a29fcaba,
  abstract     = {<p>Sensitivity analysis consists of an integral and important validatory check of a computer simulation model before the code is used in performing any kind of analysis operation. The present paper demonstrates the use of a relatively new method and tool for conducting global sensitivity analysis (GSA) for environmental models, providing simultaneously the first GSA study of the widely used 1d soil-vegetation-atmospheric transfer (SVAT) model named SimSphere. A software platform called the Gaussian emulation machine for sensitivity analysis (GEM SA), which has been developed for performing a GSA via Bayesian theory, is applied to SimSphere model in order to identify the most responsive model inputs to the simulation of key model outputs, detect their interactions and derive absolute sensitivity measures concerning the model structure. This study is also very timely in that, use of this particular SVAT model is currently being considered to be used in a scheme being developed for the operational retrieval of the soil surface moisture content by National Polar-orbiting Operational Environmental Satellite System (NPOESS), in a series of satellite platforms that are due to be launched in the next 12 years starting from 2016. The employed GSA method was found capable of identifying the most responsive SimSphere inputs and also of capturing their key interactions for each of the simulated target quantities on which the GSA was conducted. The most sensitive model inputs were the topography parameters (slope, aspect) as well as the fractional vegetation cover and soil surface moisture availability. The implications of these findings for the future use of SimSphere are discussed.</p>},
  author       = {Petropoulos, G. and Wooster, M. J. and Carlson, T. N. and Kennedy, M. C. and Scholze, M.},
  issn         = {0304-3800},
  keyword      = {BACCO GEM SA,Gaussian process emulator,Sensitivity analysis,SimSphere,SVAT model},
  language     = {eng},
  month        = {10},
  number       = {19},
  pages        = {2427--2440},
  publisher    = {Elsevier},
  series       = {Ecological Modelling},
  title        = {A global Bayesian sensitivity analysis of the 1d SimSphere soil-vegetation-atmospheric transfer (SVAT) model using Gaussian model emulation},
  url          = {http://dx.doi.org/10.1016/j.ecolmodel.2009.06.006},
  volume       = {220},
  year         = {2009},
}