3D characterization of the subsurface redox architecture in complex geological settings

Kim, Hyojin; Høyer, Anne‐Sophie; Jakobsen, Rasmus; Thorling, Lærke; Aamand, Jens; Maurya, Pradip Kumar; Christiansen, A.V.; Hansen, Birgitte

doi:10.1016/j.scitotenv.2019.133583

Cited by 21 publications

(18 citation statements)

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“…This reducing zone is present in both redox realizations (Figure 10d and Figure 10h) and hence the overall redox architecture is in place, and the difference is mainly small-scale in the extent of this zone. The layered structure of the reducing zone below the reduced zone might be explained by the geological window structure around the sandy till ( Figure 490 10d,h; Kim et al, 2019). Alternatively, unsaturated sand may be situated just below the clay till or both a vertical and horizontal flow is occurring in the meltwater sand.…”

Section: Modeling Resultsmentioning

confidence: 99%

“…In a simple case with only vertical infiltration, nitrate concentrations in aquifers decrease with an increasing depth along three sequential redox zones (Kim et al, 2019;Wilson et al, 2018): 45 1) Oxic zone: Nitrate conditions are equal to the leaching from the soil because of the oxic conditions preventing reduction 2) Nitrate reducing zone: Nitrate decrease with increasing depth due to ongoing reduction of nitrate 3) Reduced zone: Nitrate free zone due to complete reduced redox conditions The redox conditions of the subsurface has been widely investigated using various approaches focusing on different redox 50 sensitive chemical compounds such as nitrate, iron, sulphate, pyrite, organic matter, arsenic, uranium, and some organic contaminants: 1) process-based approaches (e.g. (Abbaspour et al (2007); Hansen et al (2014aHansen et al ( ,2016a; Lee et al, (2008)), 2) geostatistical methods (e.g., Kriging;Ernstsen et al (2008); Goovaerts et al (2005) ;Lin, (2008)) and 3) machine learning (Close et al, 2016;Koch et al, 2019;Nolan et al, 2015;Ransom et al, 2017;Rosecrans et al, 2017;Tesoriero et al, 2015; challenge for 3D modeling and interpretations between geological point data may lead to large uncertainties (Wellmann and Caumon, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…In Denmark, sediment colors have been widely used to interpret redox conditions (Ernstsen and von Platen, 2014;Hansen et al, 2016a;Kim et al, 2019) and these data are publicly accessible in the Jupiter database. Red, orange, yellow and combinations of these colors represent oxic conditions and gray, olive and blue colors represent reduced conditions.…”

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confidence: 99%

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3D multiple point geostatistical simulation of joint subsurface redox and geological architectures

Madsen¹,

Kim²,

Kallesøe³

et al. 2020

Preprint

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Abstract. Nitrate contamination of subsurface aquifers is an ongoing environmental challenge due to nitrogen (N) losses from intensive N fertilization and management on agricultural fields. The distribution and fate of nitrate in aquifers are primarily governed by geological, hydrological and geochemical conditions of the subsurface. Therefore, we propose a novel approach to model both geology and redox architectures simultaneously in high resolution 3D (25 m × 25 m × 2 m) using multiple point geostatistical simulation (MPS). Data consists of 1) mainly resistivities of the subsurface mapped with towed transient electromagnetic measurements (tTEM), and 2) information of lithology and redox conditions obtained from the borehole observations at point scale interpreted from the geological descriptions and colors of sediment samples, and chemistry analyses of water samples. The conceptual understandings of the geological and redox architectures of the study system were introduced to the simulation as training images. These data were combined with detailed soil maps and digital elevation models to identify main geological elements defined as volumes within the subsurface. From a geological perspective, these data are considered independent from each other in terms of formation. This approach became computationally attractive by simulating smaller geological elements individually instead of the entire catchment. The final realizations were stitched together using simulations of the individual geological elements, resulting in an ensemble of realizations representing a quantification of the uncertainty for the given setup. The joint simulation of geological and redox architectures, which is one of the strengths of the MPS simulations compared to other geostatistical methods, secures that the two architectures in general show coherent patterns. Despite the inherent subjectivity of interpretations of the training images and geological element boundaries, they enable an easy and intuitive incorporation of qualitative knowledge of geology and geochemistry in quantitative simulations of the subsurface architectures. Altogether, we conclude that our approach effectively simulates the coherent geological and redox architectures of the subsurface that can be used for hydrological modelling with N-transport, which may be fundamental to better understanding of the nitrogen (N) retention of the subsurface and to future more targeted regulation of agriculture.

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Section: Modeling Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

3D multiple point geostatistical simulation of joint subsurface redox and geological architectures

Madsen¹,

Kim²,

Kallesøe³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

“…Modeling approaches have included (1) processbased approaches (e.g., Abbaspour et al, 2007;B. Hansen, 2016;Lee et al, 2008), (2) geostatistical methods (e.g., kriging; Ernstsen et al, 2008;Goovaerts et al, 2005;Lin, 2008) and (3) machine learning (Close et al, 2016;Koch et al, 2019;Nolan et al, 2015;Ransom et al, 2017;Rosecrans et al, 2017;Tesoriero et al, 2015;Wilson et al, 2018). However, many of these approaches require large sets of data of especially groundwater chemistry, and it is costly and time-consuming to collect sufficient volumes of data.…”

Section: Introductionmentioning

confidence: 99%

3D multiple-point geostatistical simulation of joint subsurface redox and geological architectures

Madsen

Kim

Kallesøe

et al. 2021

Hydrol. Earth Syst. Sci.

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Abstract. Nitrate contamination of subsurface aquifers is an ongoing environmental challenge due to nitrogen (N) leaching from intensive N fertilization and management on agricultural fields. The distribution and fate of nitrate in aquifers are primarily governed by geological, hydrological and geochemical conditions of the subsurface. Therefore, we propose a novel approach to modeling both geology and redox architectures simultaneously in high-resolution 3D (25m×25m×2m) using multiple-point geostatistical (MPS) simulation. Data consist of (1) mainly resistivities of the subsurface mapped with towed transient electromagnetic measurements (tTEM), (2) lithologies from borehole observations, (3) redox conditions from colors reported in borehole observations, and (4) chemistry analyses from water samples. Based on the collected data and supplementary surface geology maps and digital elevation models, the simulation domain was subdivided into geological elements with similar geological traits and depositional histories. The conceptual understandings of the geological and redox architectures of the study system were introduced to the simulation as training images for each geological element. On the basis of these training images and conditioning data, independent realizations were jointly simulated of geology and redox inside each geological element and stitched together into a larger model. The joint simulation of geological and redox architectures, which is one of the strengths of MPS compared to other geostatistical methods, ensures that the two architectures in general show coherent patterns. Despite the inherent subjectivity of interpretations of the training images and geological element boundaries, they enable an easy and intuitive incorporation of qualitative knowledge of geology and geochemistry in quantitative simulations of the subsurface architectures. Altogether, we conclude that our approach effectively simulates the consistent geological and redox architectures of the subsurface that can be used for hydrological modeling with nitrogen (N) transport, which may lead to a better understanding of N fate in the subsurface and to future more targeted regulation of agriculture.

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Paleoenvironmental Dynamics in a Mesoproterozoic Epicontinental Sea, Faded Shale, Son Valley, India

Mondal

Koner

Choudhuri

et al. 2022

Geochemical Treasures and Petrogenetic Processes

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3D characterization of the subsurface redox architecture in complex geological settings

Cited by 21 publications

References 53 publications

3D multiple point geostatistical simulation of joint subsurface redox and geological architectures

3D multiple point geostatistical simulation of joint subsurface redox and geological architectures

3D multiple-point geostatistical simulation of joint subsurface redox and geological architectures

Paleoenvironmental Dynamics in a Mesoproterozoic Epicontinental Sea, Faded Shale, Son Valley, India

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