Investigation of T-H-M-C processes on sealing systems in rock salt

Meyer, Thorsten; Czaikowski, Oliver; Jantschik, Kyra

doi:10.46427/gold2022.8578

Cited by 2 publications

(3 citation statements)

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“…A spatial cross validation strategy, in which spatial units are held back for validation 272,273 , assesses the ability of the model to predict beyond the clusters, which is in line with the purpose of the model to predict into spaces that lack training data [273][274][275] . We used the k-fold Nearest Neighbour Distance Matching (k-NNDM) Cross-Validation presented by Linnenbrink et al 2023 276 and implemented within the CAST package (0.8.1) 277 , which is a variant of the leave-one-out NNDM cross validation with reduced computation time compared to the method developed by Milà et al 2022 274 . This k-NNDM method creates folds such that the geographic distance between sample points of different folds approximates the distance between the training samples and the prediction locations.…”

Section: K-nndm Cross Validationmentioning

confidence: 99%

“…data larger than the 75th percentile plus 1.5 times the interquartile range of the DI values of the cross-validated training data. The calculation of the pixel-level DI and the AOA were generated using the aoa() function, both available in the CAST package (0.8.1) 277 . Then, the predictor space which is greater than the AOA threshold is considered outside the area of applicability, and thus is masked from our predictions.…”

Section: Area Of Applicabilitymentioning

confidence: 99%

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Soil carbon in the world’s tidal marshes

Maxwell,

Spalding,

Friess

et al. 2024

Preprint

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Tidal marshes are threatened coastal ecosystems known for their capacity to store large amounts of carbon in their water-logged soils. Accurate quantification and mapping of global tidal marshes soil organic carbon (SOC) stocks is of considerable value to conservation efforts. Here, we used training data from 3,710 unique locations, landscape-level environmental drivers and a newly developed global tidal marsh extent map to produce the first global, spatially-explicit map of SOC storage in tidal marshes at 30 m resolution. We estimate the total global SOC stock to 1 m to be 1.44 Pg C, with a third of this value stored in the United States of America. On average, SOC in tidal marshes' 0-30 and 30-100 cm soil layers are estimated at 83.1 Mg C ha-1(average predicted error 44.8 Mg C ha-1) and 185.3 Mg C ha-1(average predicted error 105.7 Mg C ha-1), respectively. Our spatially-explicit model is able to capture 59% of the variability in SOC density, with elevation being the strongest driver aside from soil depth. Our study reveals regions with high prediction uncertainty and therefore highlights the need for more targeted sampling to fully capture SOC spatial variability.

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Section: K-nndm Cross Validationmentioning

confidence: 99%

Section: Area Of Applicabilitymentioning

confidence: 99%

Soil carbon in the world’s tidal marshes

Maxwell,

Spalding,

Friess

et al. 2024

Preprint

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“…Opalinus Clay (OPA) has a thickness of about 110 m and was deposited in a shallow sea with an average water depth of 20-50 m (Hostettler et al, 2017;Lauper et al, 2018). The lithology of OPA is regionally variable, and the formation is commonly subdivided into several lithofacies (e.g., Matter et al, 1987;1988;Bläsi et al, 1991;Nagra, 2001;2002;Wetzel and Allia, 2003). It is obvious, however, that Opalinus Clay alternates in composition even on the centimeter (cm) to decimeter (dm) scale (Lauper et al, 2018) as it was documented during the deep drilling campaign, among other methods through X-ray imaging.…”

Section: Introductionmentioning

confidence: 99%

XCT analysis of drill cores of Opalinus clay and determination of sample size for effective properties evaluation

Keller

2023

Front. Earth Sci.

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In Switzerland, the Opalinus Clay unit was chosen as host rock for a repository for nuclear waste and has recently been investigated in a deep drilling campaign at possible repository construction sites. X-ray images of drill cores were compiled into virtual rock columns and were statistically analyzed with respect to layered compositional variations. This provides insight into scale-dependent homogenization and improves sampling strategy. To predict the repository behavior, using continuum-based models of Opalinus Clay, requires the knowledge of effective properties related to a minimum volume at which Opalinus Clay behaves homogeneously. It turned out that with respect to rock composition, such a volume does not exist in the sense that a single sample of manageable size provides a reliable mean composition. This is because the variation of the cm to dm thick layers, which differ in composition, does not sufficiently homogenize even at the 10-m scale. Thus, effective properties must be obtained by averaging several handleable samples. Regarding the composition of Opalinus Clay at a particular location, about 30 samples, distributed over the whole thickness, with a length of about 30 cm should be measured so that the relative error of the mean value is not higher than 5%–10%. For the statistical analyses computed tomography (CT) values of X-ray data were calibrated with respect to rock composition based on laboratory measurements. The CT values are largely controlled by the respective volume fraction of calcite, quartz, and porous clay matrix. These three components form >80 vol% of the sedimentary rocks studied (also above and below Opalinus Clay). The relationship between CT value and component contents depends on the rock type. The use of data from different rock types to calibrate CT values with respect to composition can lead to erroneous results.

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Investigation of T-H-M-C processes on sealing systems in rock salt

Cited by 2 publications

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Soil carbon in the world’s tidal marshes

Soil carbon in the world’s tidal marshes

XCT analysis of drill cores of Opalinus clay and determination of sample size for effective properties evaluation

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