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FältnamnIndikatorerMetadata
00005914naa a2200541 4500
001oai:research.chalmers.se:85f8af07-62cb-4c07-9396-852090ea9aa0
003SwePub
008171007s2016 | |||||||||||000 ||eng|
009oai:gup.ub.gu.se/226687
0247 a https://doi.org/10.1016/j.enggeo.2015.11.0062 DOI
0247 a https://research.chalmers.se/publication/2266872 URI
0247 a https://gup.ub.gu.se/publication/2266872 URI
040 a (SwePub)cthd (SwePub)gu
041 a engb eng
042 9 SwePub
072 7a art2 swepub-publicationtype
072 7a ref2 swepub-contenttype
1001 a Sundell, Jonas,d 1984u Chalmers tekniska högskola,Chalmers University of Technology4 aut0 (Swepub:cth)sundellj
2451 0a A probabilistic approach to soil layer and bedrock-level modelling for risk assessment of groundwater drawdown induced land subsidence
264 1b Elsevier BV,c 2016
338 a electronic2 rdacarrier
520 a Sub-surface construction in urban areas generally involves drainage of groundwater, which can induce subsidence in soil deposits. Knowledge of where compressible sediments are located and how thick these are is essential for estimating subsidence risk. A probabilistic method for coupled bedrock-level and soil-layer modeling to detect compressible sediments is presented. The method is applied in an area in central Stockholm, where clay is the compressible sediment layer. First, a bedrock-level model was constructed from three sources of information: (a) geotechnical drillings reaching the bedrock; (b) drillings not reaching the bedrock; and (c) mapped bedrock outcrops. Input data for the probabilistic bedrock-level model was generated by a stepwise Kriging procedure. Second, a three layer soil model was constructed, including the following materials: (a) coarse grained post glacial and filling material below the ground surface; (b) glacial and post-glacial clays; and (c) coarse grained glaciofluvial and glacial till deposits above the bedrock. Layer thicknesses were transformed to proportions of the total soil thickness. Since Kriging requires data to be normally distributed, the proportions were transformed from proportions (P) to standard normal quantiles (z). In each iteration of a Monte-Carlo simulation, a spatial distribution of the bedrock level was simulated together with the transformed values for the soil-layer proportions. From the iterations, the probability density of the clay thickness (compressible sediments) at each grid cell was calculated. The results of the case study map the expected value (mean) and the 95th percentile of the probability of compressible sediments at specific locations. The resulting model is geologically realistic and validated through a cross-validation procedure in order to be in good agreement with a reference dataset. The case study showed that the method can efficiently handle large amounts of data and requires little manual adjustment. Moreover, the mapped results can provide useful decision support when planning risk-reducing measures and when communicating with stakeholders. Although this novel method is developed for risk assessment of groundwater drawdown induced subsidence, it is useful for other applications involving spatial soil strata modeling.
650 7a TEKNIK OCH TEKNOLOGIERx Samhällsbyggnadsteknikx Geoteknik0 (SwePub)201062 hsv//swe
650 7a ENGINEERING AND TECHNOLOGYx Civil Engineeringx Geotechnical Engineering0 (SwePub)201062 hsv//eng
650 7a TEKNIK OCH TEKNOLOGIERx Samhällsbyggnadsteknikx Vattenteknik0 (SwePub)201072 hsv//swe
650 7a ENGINEERING AND TECHNOLOGYx Civil Engineeringx Water Engineering0 (SwePub)201072 hsv//eng
650 7a NATURVETENSKAPx Geovetenskap och miljövetenskap0 (SwePub)1052 hsv//swe
650 7a NATURAL SCIENCESx Earth and Related Environmental Sciences0 (SwePub)1052 hsv//eng
650 7a NATURVETENSKAPx Geovetenskap och miljövetenskapx Oceanografi, hydrologi och vattenresurser0 (SwePub)105092 hsv//swe
650 7a NATURAL SCIENCESx Earth and Related Environmental Sciencesx Oceanography, Hydrology and Water Resources0 (SwePub)105092 hsv//eng
650 7a NATURVETENSKAPx Geovetenskap och miljövetenskapx Multidisciplinär geovetenskap0 (SwePub)105032 hsv//swe
650 7a NATURAL SCIENCESx Earth and Related Environmental Sciencesx Geosciences, Multidisciplinary0 (SwePub)105032 hsv//eng
653 a Probabilistic soil strata model
653 a Decision support
653 a Risk assessment
653 a Probabilistic bedrock level model
653 a Groundwater drawdown induced subsidence
653 a Decision support; Groundwater drawdown induced subsidence; Probabilistic bedrock level model; Probabilistic soil strata model; Risk assessment
7001 a Rosen, Lars,d 1962u Chalmers tekniska högskola,Chalmers University of Technology4 aut0 (Swepub:cth)rosen
7001 a Norberg, Tommy,d 1950u Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper, matematisk statistik,Department of Mathematical Sciences, Mathematical Statistics4 aut0 (Swepub:cth)tommy
7001 a Haaf, Ezra,d 1985u Gothenburg University,Göteborgs universitet,Institutionen för geovetenskaper,Department of Earth Sciences4 aut0 (Swepub:gu)xhaaez
7102 a Chalmers tekniska högskolab Institutionen för matematiska vetenskaper, matematisk statistik4 org
7730 t Engineering Geologyd : Elsevier BVg 203, s. 126-139q 203<126-139x 0013-7952
8564 u https://research.chalmers.se/publication/226687/file/226687_Fulltext.pdfx primaryx freey FULLTEXT
8564 u https://research.chalmers.se/publication/226687/file/226687_Fulltext.pdf
8564 8u https://doi.org/10.1016/j.enggeo.2015.11.006
8564 8u https://research.chalmers.se/publication/226687
8564 8u https://gup.ub.gu.se/publication/226687

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