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| Titel |
A global Bayesian sensitivity analysis of the 1d SimSphere SVAT model using the GEM-SA software |
| VerfasserIn |
G. Petropoulos, M. J. Wooster, T. N. Carlson, M. Kennedy, M. Scholze |
| Konferenz |
EGU General Assembly 2009
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 11 (2009) |
| Datensatznummer |
250019757
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| Zusammenfassung |
| Sensitivity analysis consist an integral validatory check of an all-inclusive validation of any
multi-level code computer simulation model before the latter is used in performing any kind
of analysis of operation, particularly so if a model is going to be used on an operational
basis.
A software platform/tool called GEM SA developed for performing a global
sensitivity analysis (GSA) adopting the Bayesian theory is tested herein in the 1d
SVAT model SimSphere with the aim to identify the most responsive model inputs,
detect their interactions and derive absolute sensitivity measures concerning the
model structure. The present study represents the first implementation of a global
sensitivity analysis (GSA) method in SimSphere whereas the method presented
here can be potentially adopted and applied to other simulation models including
SVAT models. This study is very timely in terms of the overall validation of the
model, considering that its use was recently proposed in modelling methodology for
the operational retrieval of surface moisture content by National Polar-orbiting
Operational Environmental Satellite System (NPOESS) and NASA in a series of
satellite platforms scheduled to be placed in orbit in the next 12 years starting from
2009.
The employed GSA method was found capable of identifying the most responsive model
inputs and also of capturing the key interactions structure between the model inputs in the
simulation of each of the target quantities on which the GSA was conducted. The dominant
input parameters which were found to consistently control the predictions of the considered
outputs by the model were the topography parameters (slope, aspect) as well as the fractional
vegetation cover and surface moisture availability. The implications of these findings for the
use of the model are also discussed.
Keywords: SimSphere, BACCO GEM-SA, SVAT model, sensitivity analysis, Gaussian
process emulator |
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