Geology
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Experience over the past 15 years has demonstrated that the use of airborne electromagnetics (AEM) for near-surface hydrogeological investigations in the Australian landscape context often requires high resolution data to map key functional elements of the hydrogeological system. Optimisation of AEM data therefore requires careful consideration of AEM system suitability, calibration, validation and inversion methods. The choice of an appropriate AEM system for a given task should be based on a comparative analysis of candidate systems, consisting of both theoretical considerations and field studies including test lines over representative hydrostratigraphic targets. In the Broken Hill Managed Aquifer Recharge (BHMAR) project, the SkyTEM AEM system was chosen, after a rigorous selection process, to map a multi-layered stratigraphy in unconsolidated sediments in the top 100 m of the River Darling Floodplain. The AEM acquisition strategy was governed by the need to rapidly identify and assess potential managed aquifer recharge (MAR) and groundwater resource targets over a large area (>7,500 km2), with a high degree of confidence. A flight line spacing of 200-300 m successfully mapped the key elements of the hydrostratigraphy, important neotectonics features, and 14 potential MAR and groundwater targets. Subsequent to successful completion of the project, the AEM data were re-inverted to assess optimal line spacings for the different mapping objectives. Data for the central project area were re-inverted, corresponding to a line spacing of 200 m, 600 m, 1 km, 2 km and 5 km. Analysis of these data show that a number of key features of the hydrogeological system required for MAR target mapping and evaluation are only mapped with high resolution (200m) line spacings. In contrast, the larger groundwater resource targets can be identified at coarser line spacings (even at km spacings). For many groundwater mapping objectives, recconaisance surveys at wide line spacings can be used to identify broad-scale features, with higher resolution data acquired subsequently to address specific questions. This strategy is not always possible in project timelines, and, in the BHMAR project, it was fortunate that a large number of targets were mapped at high resolution simultaneously due to a high failure rate in MAR evaluations.
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