Use of the Resolve Airborne Electromagnetic (AEM) Data in the Assessment of the Salinity Hazard and Risk to Iconic River and Wetland Ecosystems, Murray River, SE Australia

Abstract

An AEM survey using the RESOLVE frequency domain system has been acquired along a 450 km reach of the Murray River in SE Australia. The AEM data were inverted using the holistic inversion method, enabling key elements of the hydrogeological system in the shallow sub‐surface (top 20–50m) to be mapped with high confidence levels. The AEM data have been used in conjunction with remote sensing, and hydrogeological and hydrogeochemical data obtained from drilling, to determine that healthy vegetation along the Murray River is generally associated with the presence of significant river ‘flush zones’ where fresh groundwater is present at shallow depths, and groundwater salinity is low. The study has also found that the corollary is true: where the river is ‘gaining’, and salt stores are high, vegetation health is generally in decline. Similarly, the AEM data show there is a marked decline in vegetation health towards the western edge of the iconic Gunbower State Forest. This appears to be associated with salt being mobilised from irrigation districts on the western margins of the Gunbower Forest. In the areas where the river flush zones are discontinuous, and the salt stores and water tables are closer to surface, there is also a risk of salt ingress to the river. In these areas, the data identify areas for targeted salinity management, including sites for potential Salt Interception Schemes. This study fills important knowledge gaps particularly the distribution of key elements of the hydrostratigraphy, salinity extent, and the relationships between vegetation health, salinity and groundwater processes. In particular, the project has successfully integrated AEM, remote sensing, and lithological and hydrogeological data from drilling, to identify reaches of the River Murray and areas of iconic wetland ecosystems at risk from groundwater salinisation. These datasets provide geospatial context for targeted salinity and groundwater management actions.