4.5 Article

DInSAR data assimilation for settlement prediction: case study of a railway embankment in the Netherlands

Journal

CANADIAN GEOTECHNICAL JOURNAL
Volume 54, Issue 4, Pages 502-517

Publisher

CANADIAN SCIENCE PUBLISHING
DOI: 10.1139/cgj-2016-0425

Keywords

settlement prediction; data assimilation; DInSAR; embankment; soft soils

Funding

  1. Deltares
  2. SkyGeo through the Climate-KIC program
  3. ERASMUS+ programme

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Secondary settlements in soft soils represent a significant fraction of the total settlement induced by external loads. Consequently, these settlements can play a key role in performance, serviceability, and safety of engineering works such as buildings, roads, embankments, and pipelines. This paper addresses the development of a predictive settlement model for a railway embankment built on soft clayey-peaty soils by following an original procedure consisting of three cascading steps: (i) preliminary detection of the most settlement-affected portions of the infrastructure; (ii) development of an equivalent subsoil model to study secondary settlements; (iii) back-calculation of the parameters of a predictive settlement model (design subsoil model) via a variational data assimilation scheme that exploits ground displacement measurements derived from differential interferometric synthetic aperture radar (DInSAR) data. The main achievement relies on the retrieval of a stochastic prediction of secondary settlements that can contribute to rationalize both conventional monitoring campaigns and management of key infrastructure.

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