In urban landscapes, information is required to describe the heterogeneous nature of pedological and hydrological resources. This is particularly the case in areas previously used as municipal landfills. Increasingly, geophysical techniques such as electromagnetic (EM) induction are being used. Here we describe how a single‐frequency and multiple‐coil EM instrument can be used in conjunction with a one‐dimensional spatially constrained quasi‐three‐dimensional inversion algorithm to map electrical conductivity (σ). The algorithm is briefly described and then applied to soil apparent electrical conductivity (σa) data observed with a DUALEM‐421 and across a former municipal landfill at Astrolabe Park in Daceyville, Sydney. The results are presented as isosurface maps of σ. In general, the results compare favorably with existing knowledge and previous research results performed within a highly modified aeolian sand landscape. Specifically, the isosurface maps allow us to discern a gradient in, as well as identify contiguous corridors of, σ, which allow us to infer the likely location of leachate plume flow paths and their origin. The results demonstrate how EM instruments can provide rapid measurements of σa. In addition, coupled to a one‐dimensional spatially constrained quasi‐three‐dimensional inversion algorithm, the data enable robust estimates of σ, which may be useful for informing future natural resource management and research needs in a decommissioned municipal landfill at Astrolabe Park, which is impacted by a leachate plume.

In coastal-estuarine agricultural landscapes that are inherently rich in sulfidic sediments and saline water-tables, natural resource management data need to be collected to describe the heterogeneous nature of the soil, underlying regolith, and interactions with groundwater. Geophysical methods, such as electromagnetic (EM) induction instruments, are increasingly being used. This is because they measure apparent soil electrical conductivity [Formula: see text], which has previously been successfully used to map the areal distribution of soil (e.g., salinity) and hydrological (e.g., water-table depth) properties. We explored the potential of a next-generation DUALEM-421 and EM34 to be used independently and in conjunction with each other to provide information we can use to represent the pedological and hydrogeological setting of alluvial and estuarine sediments. A 1D laterally constrained joint-inversion algorithm can account for the nonlinearity of large [Formula: see text] (i.e., [Formula: see text]). We applied this algorithm to develop 2D cross sections of electrical conductivity ([Formula: see text]) from DUALEM-421 and EM34 [Formula: see text] data acquired across an estuarine landscape and situated within Quaternary fluvial sediments adjacent to Rocky Mouth Creek on the far north coast of New South Wales, Australia. We compared this joint-inversion model with inversions of the DUALEM-421 and EM34 [Formula: see text] data independently of each other. For the most part, the general patterns of the inverted models of [Formula: see text] compare favorably with existing pedological and hydrogeological interpretations, based on results achieved during a previous geoelectrical survey. However, the joint-inversion provides a more realistic model of the location and extent of a saline water-table and associated with the location of sulfidic sediments.

Two‐thirds of all irrigated agriculture in Australia is undertaken within the Murray–Darling Basin. However, climate change predictions for this region suggest rainfall will decrease. To maintain profitability, more will need to be done by irrigators with less water. In this regard, irrigators need to be aware of the spatial distribution of the available water content (AWC) in the root‐zone (i.e. 0.0–0.90 m). To reduce the cost, digital soil mapping (DSM) techniques are being used to map soil properties related to AWC (e.g. soil texture). The purpose of this study was to create a DSM of the AWC at the district scale. This is achieved by determining AWC by the difference between laboratory measured permanent wilting point (PWP) and field capacity (FC) and using pressure plate apparatus. The PWP and FC data are coupled to remote (i.e. gamma‐ray spectrometry) and proximal (i.e. EM38 and EM34) sensed data and two trend surface parameters. Using a hierarchical spatial regression (HSR), we predict PWP and FC across the areas of Warren and Trangie in the lower Macquarie valley, Australia. The reliability of the DSM of PWP and FC were compared using prediction precision (RMSE – root mean square error) and bias (ME – mean error). The best results were achieved using EM38‐v, EM34‐20, eU and eTh. The DSM map of AWC is consistent with known Pedoderms and provides a basis for agricultural water management.

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