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Testing of a GIS model ofEucalyptus Iargiflorens health on a semiarid,saline floodplain
Authors:Peter J Taylor  Glen R Walker  Geoff Hodgson  Thomas J Hatton  Ray L Correll
Institution:(1) CSIRO Division of Water Resources, PMB 2, 5064 Glen Osmond, SA, Australia;(2) CSIRO Division of Water Resources, GPO Box 1666, 2601 Canberra, ACT, Australia;(3) Biometrics Unit, CSIRO Institute of Natural Resources & Environment, PMB 2, 5064 Glen Osmond, SA, Australia;(4) Present address: Department of Agronomy & Farming Systems, University of Adelaide, 5371 Roseworthy, South Australia, Australia
Abstract:Irrigated agriculture has resulted in substantial changes in water flows to the lower reaches of the River Murray. These changes have led to large-scale occurrences of dieback inEucalyptus largiflorens (black box) woodlands as well as increased inputs of salt to the river. Management options to address problems of this scale call for the use of spatial data sets via geographic information systems (GIS). A GIS exists for one floodplain of the River Murray at Chowilla, and a simple model predicted six health classes ofEucalyptus largiflorens based on groundwater salinity, flooding frequency, and groundwater depth.To determine the usefulness of the model for vegetation management, the quality of both the model and the GIS data sets were tested. Success of the testing procedure was judged by the degree of spatial matching between the model's predictions of health and that assessed from aerial photographs and by field truthing. Analyses at 80 sites showed that tree health was significantly greater where groundwater salinity was less than 40 dS/m or flooding occurred more frequently than 1 in 10 years or depth to groundwater exceeded 4 m. Testing of the GIS data sets found that vegetation was misclassified at 15% of sites. Association was shown between GIS-predicted values and field-truthed values of groundwater salinity but not groundwater depth. The GIS model of health is a useful starting point for future vegetation management and can be further improved by increasing the quality of the data coverages and further refining of the model to optimize parameters and thresholds.
Keywords:Geographic information systems  Model validation  Floodplain vegetation  Vegetation health
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