2016
DOI: 10.1007/s10040-016-1513-9
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Interlobate esker architecture and related hydrogeological features derived from a combination of high-resolution reflection seismics and refraction tomography, Virttaankangas, southwest Finland

Abstract: A novel high-resolution (2-4 m source and receiver spacing) reflection and refraction seismic survey was carried out for aquifer characterization and to confirm the existing depositional model of the interlobate esker of Virttaankangas, which is part of the Säkylänharju-Virttaankangas glaciofluvial esker-chain complex in southwest Finland. The interlobate esker complex hosting the managed aquifer recharge (MAR) plant is the source of the entire water supply for the city of Turku and its surrounding municipalit… Show more

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Cited by 16 publications
(37 citation statements)
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References 67 publications
(78 reference statements)
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“…Maries et al . () showed seismic facies of arched geometry and high amplitudes as well as dimensions of 100 m length and 20 m height, which is comparable to the eskers that we found in profile 3. The eskers described by Maries et al .…”
Section: Discussionsupporting
confidence: 87%
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“…Maries et al . () showed seismic facies of arched geometry and high amplitudes as well as dimensions of 100 m length and 20 m height, which is comparable to the eskers that we found in profile 3. The eskers described by Maries et al .…”
Section: Discussionsupporting
confidence: 87%
“…The eskers described by Maries et al . () appear to be more elongated (250 m) than in our sections, however this is probably because of the oblique cut, with regard to an assumed main ice flow direction toward the north. Pugin et al .…”
Section: Discussioncontrasting
confidence: 73%
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“…; Maries et al . ). For each sample, we compute seismic responses from multiple source locations and couple simulations with deep learning for the prediction of water‐table level and the amount of stored water.…”
Section: Introductionmentioning
confidence: 99%
“…We use a Gaussian process to generate samples from the potential scenarios for the aquifer for both the material model and the geometry. The prior information for the aquifer system is based on earlier studies and traditional ray-tracingbased estimates (Artimo et al 2003;Maries et al 2017). For each sample, we compute seismic responses from multiple source locations and couple simulations with deep learning for the prediction of water-table level and the amount of stored water.…”
Section: Introductionmentioning
confidence: 99%