A detection problem: sensitivity and uncertainty analysis of a land surface temperature approach to detecting dynamics of water use by groundwater-dependent vegetation

Gow, L. J., Barrett, D. J., Renzullo, L. J., Phinn, S. R. and O'Grady, A. P. (2016) A detection problem: sensitivity and uncertainty analysis of a land surface temperature approach to detecting dynamics of water use by groundwater-dependent vegetation. Environmental Modelling and Software, 85 342-355. doi:10.1016/j.envsoft.2016.09.003


Author Gow, L. J.
Barrett, D. J.
Renzullo, L. J.
Phinn, S. R.
O'Grady, A. P.
Title A detection problem: sensitivity and uncertainty analysis of a land surface temperature approach to detecting dynamics of water use by groundwater-dependent vegetation
Journal name Environmental Modelling and Software   Check publisher's open access policy
ISSN 1364-8152
1873-6726
Publication date 2016-11-01
Year available 2016
Sub-type Article (original research)
DOI 10.1016/j.envsoft.2016.09.003
Open Access Status Not yet assessed
Volume 85
Start page 342
End page 355
Total pages 14
Place of publication Kidlington, Oxford, United Kingdom
Publisher Pergamon Press
Collection year 2017
Language eng
Formatted abstract
Sustainable management of groundwater-dependent vegetation (GDV) requires the accurate identification of GDVs, characterisation of their water use dynamics and an understanding of associated errors. This paper presents sensitivity and uncertainty analyses of one GDV mapping method which uses temperature differences between time-series of modelled and observed land surface temperature (LST) to detect groundwater use by vegetation in a subtropical woodland. Uncertainty in modelled LST was quantified using the Jacobian method with error variances obtained from literature. Groundwater use was inferred where modelled and observed LST were significantly different using a Student's t-test. Modelled LST was most sensitive to low-range wind speeds (<1.5 m s−1), low-range vegetation height (<=0.5 m), and low-range leaf area index (<=0.5 m2 m−2), limiting the detectability of groundwater use by vegetation under such conditions. The model-data approach was well-suited to detection of GDV because model-data errors were lowest for climatic conditions conducive to groundwater use.
Keyword Groundwater-dependent vegetation
Land surface temperature
Sensitivity analysis
Surface energy balance modelling
Uncertainty analysis
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Geography, Planning and Environmental Management Publications
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