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

摘要: 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 generating relevant land water resource information for integrated regional salinity. In this paper relationships between patterns in use/cover distribution base flow salt concentration streams (indicated by EC) are investigated modelled. The Glenelg-Hopkins area large watershed southwest Victoria, Australia, covering approximately 2.6 million ha. It currently estimated that 27,400 ha affected predicted rapidly increase next decade if current conditions prevail. Salt data from five gauging stations were analysed with multi-temporal use maps obtained imagery. Multiple regression analyses demonstrated variables Native Vegetation Dryland Grain Cropping most significant influences in-stream whole catchment (r2=88.9%) 500 m (r2=88.3%) 100 riparian buffers (r2=86.9%) during times flow. The implications for future planning, effectiveness zones revegetation programmes discussed. This work also demonstrates utility applying multivariate statistical analyses, spatial statistics, remote sensing framework the purpose predicting managing threat.