Multivariate modelling of landuse on in-stream salinity over multiple spatial scales

Versace, V., Ierodiaconou, Daniel, Salzman, Scott, Stagnitti, Frank, Leblanc, M., Boland, A., Laurenson, Laurie, March, T. and Thwaites, L. 2005, Multivariate modelling of landuse on in-stream salinity over multiple spatial scales. In De Conceicao Cunha, M. and Brebbia, C. A. (ed), Water resources management III, WIT Press, Southampton, England, pp.299-309.

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Title Multivariate modelling of landuse on in-stream salinity over multiple spatial scales
Author(s) Versace, V.ORCID iD for Versace, V.
Ierodiaconou, DanielORCID iD for Ierodiaconou, Daniel
Salzman, ScottORCID iD for Salzman, Scott
Stagnitti, Frank
Leblanc, M.
Boland, A.
Laurenson, LaurieORCID iD for Laurenson, Laurie
March, T.
Thwaites, L.
Title of book Water resources management III
Editor(s) De Conceicao Cunha, M.
Brebbia, C. A.
Publication date 2005
Series WIT transactions on ecology and the environment ; v.80
Total chapters 67
Start page 299
End page 309
Total pages 11
Publisher WIT Press
Place of Publication Southampton, England
Keyword(s) dryland salinity
salt concentration
remote sensing
multiple regression
land use
Summary An impediment to sustainable dryland salinity management is the lack of information on contributing factors. GIS and satellite imagery now offer a cost-effective means of generating relevant land and water resource information for integrated regional management of salinity. In this paper the relationships between patterns in land uselcover distribution and base flow salt concentration in streams (indicated by EC) are investigated and modelled. The Glenelg-Hopkins area is a large regional watershed in southwest Victoria, Australia, covering approximately 2.6 million ha. It is currently estimated that 27,400 ha of land is affected by dryland salinity and this is predicted to rapidly increase in the next decade' if current conditions prevail. Salt concentration data from five gauging stations were analysed with multi-temporal land use maps obtained from satellite imagery. Multiple regression analyses demonstrated that the variables Native Vegetation and Dry/and Grain Cropping were the most significant influences on in~stream salinity in the whole catchment (1=88.9%) and 500 m V=88.3%) and 100 m riparian buffers (1=86.9%) during times of base flow. The implications for future land use planning, effectiveness of riparian zones and revegetation programmes is discussed. This work also demonstrates the utility of applying nmltivariate statistical analyses, spatial statistics, and remote sensing with data integrated in a GIS framework for the purpose of predicting and managing the regional salinity threat.
ISBN 1845640071
ISSN 1743-3541
Language eng
Field of Research 090702 Environmental Engineering Modelling
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category B1 Book chapter
Copyright notice ©2005, WIT Press
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