Airborne and ground‐based transient electromagnetic mapping of groundwater salinity in the Machile–Zambezi Basin, southwestern Zambia

Chongo, Mkhuzo; Christiansen, Anders Vest; Tembo, Alice; Banda, Kawawa; Nyambe, Imasiku; Larsen, Flemming; Bauer‐Gottwein, Peter

doi:10.3997/1873-0604.2015024

Cited by 23 publications

(16 citation statements)

References 38 publications

(93 reference statements)

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“…Airborne EM is especially suited to these kind of surveys, as the electrical conductivity of the subsurface is determined by properties of (1) the porous medium, such as porosity and the electrical conductivity of the grains and (2) the pore water, such as its volumetric content and its salinity (Kirsch 2006). The airborne EM systems currently in use have been shown to yield good results when compared to ground-based geophysical and borehole measurements (Chongo et al 2015, De Louw et al 2011, Fitterman and Deszcz-Pan 1998, Pedersen et al 2017, Rasmussen et al 2013Steuer et al 2009, Sulzbacher et al 2012.…”

Section: Introductionmentioning

confidence: 99%

Large-scale, probabilistic salinity mapping using airborne electromagnetics for groundwater management in Zeeland, the Netherlands

Delsman

Baaren

Siemon

et al. 2018

Environ. Res. Lett.

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Seawater intrusion has often resulted in scarce fresh groundwater resources in coastal lowlands. Careful management is essential to avoid the overexploitation of these vulnerable fresh groundwater resources, requiring detailed information on their spatial occurrence. Airborne electromagnetics (EM) has proved a valuable tool for efficient mapping of ground conductivity, as a proxy for fresh groundwater resources. Stakeholders are, however, interested in groundwater salinity, necessitating a translation of ground conductivity to groundwater salinity. This paper presents a methodology to construct a high-resolution (50 × 50 × 0.5 m 3 ) 3D voxel model of groundwater chloride concentration probability, based on a large-scale (1800 km 2 , 9640 flight line kilometres) airborne EM survey in the province of Zeeland, the Netherlands. Groundwater chloride concentration was obtained by combining pedotransfer functions with detailed lithological information. The methodology includes a Monte Carlo based forward uncertainty propagation approach to quantify the inherent uncertainty in the different steps. Validation showed good correspondence both with available groundwater chloride analyses, and with ground-based hydrogeophysical measurements. Our results show the limited occurrence of fresh groundwater in Zeeland, as 75% of the area lacks fresh groundwater within 15 m below ground surface. Fresh groundwater is mainly limited to the dune area and sandy creek ridges. In addition, significant fresh groundwater resources were shown to exist below saline groundwater, where infiltration of seawater during marine transgressions was hindered by the presence of clayey aquitards. The considerable uncertainty in our results highlights the importance of applying uncertainty analysis in airborne EM surveys. Uncertainty in our results mainly originated from the inversion and the 3D interpolation, and was largest at transition zones between fresh and saline groundwater. Reporting groundwater salinity instead of ground conductivity facilitated the rapid uptake of our results by relevant stakeholders, thereby supporting the necessary management of fresh groundwater resources in the region.

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Section: Introductionmentioning

confidence: 99%

Large-scale, probabilistic salinity mapping using airborne electromagnetics for groundwater management in Zeeland, the Netherlands

Delsman

Baaren

Siemon

et al. 2018

Environ. Res. Lett.

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“…Salinity = mapping of saline distributions or salinity interfaces. (Auken et al, ; Ball et al, ; Bedrosian et al, ; Brodie et al, ; Chongo et al, ; De Louw et al, ; Delsman et al, ; Faneca Sànchez et al, ; Fitterman & Deszcz‐Pan, ; Gunnink et al, ; Haider et al, ; He et al, ; Herckenrath et al, ; Hill, ; Jørgensen et al, ; Rasmussen et al, ; Sengpiel and Fluche, 1992; Siemon, Auken, et al, ; Siemon, Christiansen, et al, ; Siemon et al, ; Wynn, ).…”

Section: Introductionunclassified

“…Early AEM programs include mapping the fresh‐saline groundwater interface over a small island in the North Sea (Sengpiel & Meiser, ), and later a more advanced AEM system was used to map fresh groundwater in Pakistan (Sengpiel and Fluche, ). These methods have since been successfully applied for groundwater mapping campaigns across the world (e.g., Auken et al, ; Chongo et al, ; Fitterman & Deszcz‐Pan, ; Siemon et al, ). In the Netherlands, the technique was used in 2009 over the island of Schouwen‐Duivenland (Faneca Sànchez et al, ) and again in 2014–2015 covering the entire province of Zeeland (Delsman et al, ).…”

Section: Introductionmentioning

confidence: 99%

“…As well as a regularization term, layered half‐space inversions require a conceptualized model of the subsurface, or a starting model, where the Earth is discretized into a set number of layers, each of which are given property and thickness values. Starting models can be based on prior knowledge, such as known (hydro) geological boundaries (Brodie et al, ), or automatically generated based on observed data using sounding curves (Delsman et al, ; Gunnink et al, ; Sengpiel & Siemon, ); mostly, however, these are based on a simplified conceptual model of the subsurface (Auken et al, ; Bedrosian et al, ; Chongo et al, ). The type of inversion, starting model, and inversion parameter settings relating to the regularization term will affect the inversion's outcome.…”

Section: Introductionmentioning

confidence: 99%

“…Structural = mapping of hydrological units. Salinity = mapping of saline distributions or salinity interfaces (Auken et al, 2008;Ball et al, 2010;Bedrosian et al, 2013;Brodie et al, 2004;Chongo et al, 2015;De Louw et al, 2011;Delsman et al, 2018;Faneca Sànchez et al, 2012;Fitterman & Deszcz-Pan, 2004;Gunnink et al, 2012;Haider et al, 2014;He et al, 2014;Herckenrath et al, 2013;Hill, 2011;Jørgensen et al, 2012;Rasmussen et al, 2013;Sengpiel and Fluche, 1992;Siemon et al, 2015;Wynn, 2005)…”

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confidence: 99%

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Quantifying Geophysical Inversion Uncertainty Using Airborne Frequency Domain Electromagnetic Data—Applied at the Province of Zeeland, the Netherlands

King

Essink

Karaolis

et al. 2018

Water Resources Research

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An accurate understanding of the fresh‐saline distribution of groundwater is necessary for effective groundwater management. Airborne electromagnetic (AEM) surveys offer a rapid and cost‐effective method with which to map this, offering valuable additional information about the subsurface. To convert AEM data into electric conductivity and ultimately groundwater salinity, an inversion is undertaken. A number of algorithms are available for this purpose; however, these are affected by significant uncertainty, owing to inherent nonunique characteristics of this process. The most commonly used inversion codes in hydrogeophysical studies were quantitatively tested using frequency domain AEM and ground data from the province of Zeeland, the Netherlands. These include UBC1DFM code and quasi‐2D laterally constrained inversions. Following an investigation of inversion parameter settings, data were inverted for four inversion methods and interpolated into 3‐D volumes. Using geological data and empirical electrical conductivity and water salinity relationships, each inversion was converted into groundwater electrical conductivity and split into fresh‐brackish‐saline regions. For groundwater volume estimates out of a total volume of 2.8 billion m3, a fresh groundwater estimate could differ by as much as 178 million m3, depending on the inversion used. The primary factor here was the choice of model smoothness, which was shown to affect the thickness of the brackish interval. Fresh‐brackish‐saline interfaces were consistently mapped with an accuracy of ~3 m, the brackish being the most accurately resolved. The few layer method was less successful at resolving smoothly varying salinity distributions but more successful at mapping the brackish interface at greater depth.

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Evaluating the impact of correlated noise for time‐lapse transient electromagnetic (TEM) monitoring studies

McLachlan,

Christiensen,

Grombacher

et al. 2023

Near Surface Geophysics

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Typically, transient electromagnetic (TEM) hydrogeological applications focus on spatial characterization. However, there is scope for utilizing time‐lapse TEM to monitor dynamic processes. Changes related to hydrogeological processes are subtle; consequently, measurements must be of exceptional quality, and the presence and influence of noise sources must be well understood. A potentially problematic noise source is radio waves operating in the 3–300 kHz range, as they introduce correlated error into TEM measurements. For instance, it was anticipated that such radio waves could introduce smooth perturbations in the data that could be erroneously interpreted in the TEM inversion results. This work evaluates the presence of correlated noise sources, their temporal dependence and their significance for TEM monitoring. This work combines fully sampled data and normalized covariance matrices of gated data to identify correlated noise sources. Radio signals operating in the low and very low frequency (LF and VLF) bands were found to vary across the investigation period; however, their influence on the TEM inversion results was minimal. Measurement stacking remains an effective way to improve the signal‐to‐noise ratio of TEM data affected by LF and VLF noise sources as they do not introduce bias, for example smooth perturbation, into the TEM data explored in this work.

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Airborne and ground‐based transient electromagnetic mapping of groundwater salinity in the Machile–Zambezi Basin, southwestern Zambia

Cited by 23 publications

References 38 publications

Large-scale, probabilistic salinity mapping using airborne electromagnetics for groundwater management in Zeeland, the Netherlands

Large-scale, probabilistic salinity mapping using airborne electromagnetics for groundwater management in Zeeland, the Netherlands

Quantifying Geophysical Inversion Uncertainty Using Airborne Frequency Domain Electromagnetic Data—Applied at the Province of Zeeland, the Netherlands

Evaluating the impact of correlated noise for time‐lapse transient electromagnetic (TEM) monitoring studies

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