Groundwater and surface water are hydraulically connected in many landscapes, and a better understanding of their connectivity is critical for effective management of water resources. Environmental tracers are a useful preliminary tool to study the interaction between groundwater and surface water and provide independent means for corroborating or refuting information based on more traditional investigations. This paper discusses the results of using major ions, stable isotopes (deuterium and oxygen-18) and a radioactive isotope (radon-222) as environmental tracers to better understand groundwater–surface water interactions in the Border Rivers catchment, Australia. In the upstream reaches of the catchment, shallow groundwater close to the river has a similar major-ion and stable-isotope chemistry to that of the river water, and is different to the groundwater distant from the river. The near-stream groundwater has an enriched isotopic signature (less negative) whereas groundwater far from the river has a depleted isotopic signature. Overall, the comparison of chloride concentrations with deuterium suggests that three types of groundwater occur in the Border Rivers catchment: (i) the near-stream groundwaters influenced by direct recharge from the river; (ii) the groundwaters marginal to the river that are more influenced by diffuse rainfall recharge; and (iii) saline groundwaters in the downstream part of the catchment which never (or rarely) receive recharge from surface water. River water samples obtained during the high-flow season show a very low variation in radon concentrations (0.11–0.39 Bq/L). The longitudinal transect of radon concentration measurements in river water during the high-flow season indicates that there is no groundwater contribution to stream flow. Radon concentrations are lower in groundwater close to the rivers and increase with distance from the river, in general coincidence with the salinity and chloride concentration. This indicates river water infiltration into nearby alluvial aquifers, rather than groundwater discharge to the river. The results of hydrochemical and environmental isotope sampling indicate that in the upper catchment area (upstream of Keetah) the river is connected to and actively recharges the near-stream shallow alluvial aquifer. Using the environmental isotope data, we have also demonstrated that recharge of the alluvial aquifers by surface water occurs by bank infiltration, with diffuse recharge during high-rainfall events more dominant further away from the river. This information would be useful for a better understanding of the nature and extent of hydrogeological processes at the river–aquifer interface and their links with biogeochemical processes and ultimately water allocation policies.
Inverted RESOLVE FDEM data for the Bookpurnong stretch of the River Murray, were compared with the Insteam NanoTEM data and available river-bed core data. The AEM data were not collected along the river itself, but extracted from gridded profile data flown in a WNW-ESE direction. The HEM data show very similar trends in conductivity variation identified in the corresponding NanoTEM data as shown in Figures 1 and 2. There are some minor differences between the two images shown in Figure 1, but this is attributed to the NanoTEM data representing the conductivity of riverbed sediments, whereas the RESOLVE data represents the 1.5-3 metre depth from the waterlevel surface of the river. The inverted conductivity depth sections shown in Figure 2 provide a better means of comparing the two techniques. For this reach of the river the RESOLVE HEM and NanoTEM data effectively map gaining and losing stream conditions and provide significant insight into the interplay between an irrigation induced groundwater mound, the regional groundwater system and river salinity. Regolith 2006 - Consolidation and Dispersion of Ideas
High-resolution hydrogeophysical data are increasingly acquired as part of investigations to underpin groundwater mapping. However, optimization of AEM data requires careful consideration of AEM system suitability, calibration, validation and inversion methods.In modern laterally-correlated inversions of AEM data, the usefulness of the resulting inversion models depends critically on an optimal choice of the vertical and horizontal regularization of the inversion. Set the constraints too tight, and the resulting models will become overly smooth and potential resolution is lost. Set the constraints too loose, and spurious model details will appear that have no bearing on the hydrogeology. There are several approaches to an automatic choice of the regularization level in AEM inversion based predominantly on obtaining a certain pre-defined data misfit with the smoothest possible model.However, we advocate a pragmatic approach to optimizing the constraints by an iterative procedure involving all available geological, hydrogeological, geochemical, hydraulic and morphological data and understanding. In this approach, in a process of both confirming and negating established interpretations and underlying assumptions, the inversion results are judged by their ability to support a coherent conceptual model based on all available information. This approach has been essential to the identification and assessment of MAR and groundwater extraction options in the Broken Hill Managed Aquifer Recharge project.
The Ord Valley Airborne Electromagnetics (AEM) Interpretation Project was co-funded by the Australian Government and the Western Australian Government to provide information in relation to salinity and groundwater management in the Ord River Irrigation Area (ORIA). The project area covers the existing ORIA Stage 1, and the ORIA Stage 2 areas earmarked for irrigation extension. The project included the acquisition of 5,936 line km of AEM data acquired using the SKYTEM time domain system.
The Ord Valley Airborne Electromagnetics (AEM) Interpretation Project was co-funded by the Australian Government and the Western Australian Government to provide information in relation to salinity and groundwater management in the Ord River Irrigation Area (ORIA). The project area covers the existing ORIA Stage 1, and the ORIA Stage 2 areas earmarked for irrigation extension. The project included the acquisition of 5,936 line km of AEM data acquired using the SKYTEM time domain system.The SkyTEM AEM system successfully mapped key elements of the hydrogeological system over most of the project area. In general terms, the modelled conductivity structure defined from the SkyTEM smooth model Layered Constrained Inversion (LCI) matches that defined from available bore data exceptionally well, with an adjusted R2 = 0.843 determined.Overall, the AEM survey has provided enhanced spatial delineation of key elements of the hydrostratigraphy in 3D, including sand- and gravel-filled palaeochannels, and clay and silt distribution, as well as salt stores and groundwater quality. The study found significant areas of high salinity hazard in several of the Stage 2 areas earmarked for irrigation development, with salt stores and groundwater salinity often higher than in the Stage 1 areas.This study has demonstrated the effective role that AEM methods can play as part of a ‘hydrogeological systems’ approach to the management of groundwater in existing and future irrigation developments in Northern Australia. The study has also demonstrated the potential for ‘calibrated’ AEM systems and Fast Approximate Inversion software to significantly shorten AEM project timelines.Engineering and Community• Geophysics role in increasing innovative engineering opportunities• Better delineating groundwater resources• Case histories in environmental geophysics37C11LUI7
A "holistic" method for simultaneously estimating conductivity and calibration models from 1-D inversion of time-domain airborne electromagnetic (AEM) data is proposed. The work extends the concept of holistic inversion that been successfully applied to frequency-domain AEM data. The entire multi-component airborne dataset and available independent conductivity and interface-depth data are simultaneously inverted. A spline-based conductivity model covering the complete survey area is estimated. Unmonitored elements of the system geometry are included as unknown parameters of the calibration model and are solved for in the inversion.Conventional 1-D inversion methods invert each airborne sample in isolation from other samples. However, by simultaneously considering all of the available information together in a holistic inversion formulation, we are able to exploit the inter-component and spatial coherency characteristics of the airborne data. The formulation ensures that the conductivity and calibration models are optimal with respect to the airborne data and prior information.
Summary Experience over the past 15 years has demonstrated that the use of airborne electromagnetics (AEM) for near-surface hydrogeological investigations often requires high resolution data to map key functional elements of the hydrogeological system. In the Broken Hill Managed Aquifer Recharge (BHMAR) project, the AEM acquisition strategy was governed by the need to rapidly identify and assess a number of potential managed aquifer recharge (MAR) and groundwater resource targets over a large area (>7,500 km2) of the Lower Darling Valley, with a high degree of confidence, and in very short timeframes. A flight line spacing of 200–300m successfully mapped the key elements of the hydrostratigraphy, neotectonic features, and 14 potential MAR and groundwater targets. Subsequently, AEM data were re-inverted, enabling comparison of line spacing of 200 m, 600 m, 1 km, 2 km, 5 km and 10 km. Utilising the information gained from this exercise, a novel survey design was developed using a systems analysis approach incorporating a range of conceptual hydrogeological and geological models, morphotectonic and structural mapping, and temporal remote sensing and hydrogeological data. Trialling this approach, a few widely-spaced AEM transects identified potential new groundwater resources over a large area of the Middle- and Upper- Darling River Valley.
'/%3e%3c/defs%3e%3cpath fill='%23012169' d='M0 0h10080v5040H0z'/%3e%3cpath stroke='%23fff' stroke-width='.6' d='m0 0 6 3m0-3L0 3' clip-path='url(%23b)' transform='scale(840)'/%3e%3cpath stroke='%23e4002b' stroke-width='.4' d='m0 0 6 3m0-3L0 3' clip-path='url(%23c)' transform='scale(840)'/%3e%3cpath stroke='%23fff' stroke-width='840' d='M2520 0v2520M0 1260h5040'/%3e%3cpath stroke='%23e4002b' stroke-width='504' d='M2520 0v2520M0 1260h5040'/%3e%3cg fill='%23fff'%3e%3cuse xlink:href='%23d' x='2520' y='3780'/%3e%3cuse xlink:href='%23a' x='7560' y='4200'/%3e%3cuse xlink:href='%23a' x='6300' y='2205'/%3e%3cuse xlink:href='%23a' x='7560' y='840'/%3e%3cuse xlink:href='%23a' x='8680' y='1869'/%3e%3cuse xlink:href='%23e' x='8064' y='2730'/%3e%3c/g%3e%3c/svg%3e)
