Disentangling and Parameterizing Shallow Sources of Subsidence: Application to a Reclaimed Coastal Area, Flevoland, the Netherlands

The natural surface area of many coastal and delta plains has been increased by land reclamation in response to growing populations. These reclaimed lands are often experiencing subsidence. The reclaimed South Flevopolder in the coastal plain of the Netherlands has experienced severe subsidence afte...

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Bibliographic Details
Published in:Journal of geophysical research. Earth surface 2019-05, Vol.124 (5), p.1099-1117
Main Authors: Fokker, Peter A., Gunnink, Jan L., Koster, Kay, Lange, Ger
Format: Article
Language:English
Subjects:
Aeration
Clay
Coastal plains
Coastal zone
compaction
Compression
Confidence
Covariance matrix
Data assimilation
Data collection
Elevation
Groundwater
Groundwater levels
Land reclamation
Mathematical models
Oxidation
Parameter estimation
Parameters
peat oxidation
Plains
Shrinkage
Solifluction
Stochastic methods
Stochasticity
Subsidence
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Summary:The natural surface area of many coastal and delta plains has been increased by land reclamation in response to growing populations. These reclaimed lands are often experiencing subsidence. The reclaimed South Flevopolder in the coastal plain of the Netherlands has experienced severe subsidence after its reclamation in 1968. The subsidence is caused by phreatic groundwater level lowering and the associated aeration of the former subaqueous shallow subsurface and increased effective stresses. In this study, surface elevation measurements that quantify the subsidence, conducted annually between 1968 and 1993, and in 2009 and 2012, have been used to constrain and estimate the parameters in models that describe subsidence. For the estimation an Ensemble Smoother with Multiple Data Assimilation was employed. For the forward models, we employed correlations for compression (primary consolidation and creep), oxidation, and shrinkage of coastal deposits. Shrinkage of the aerated clay and organic clay layers was found to be the main contributor to subsidence, and the measurements could be represented well. The quantification of the model parameters allows for better subsidence forecasts. The stochastic method that was employed further facilitates to define a quality measure for forecasts in terms of a covariance matrix or a confidence range. Key Points Annual subsidence measurements were used for compression parameter estimation An Ensemble Smoother with Multiple Data Assimilation was employed Shrinkage of clay and organic clay was found the main contributor to compression
ISSN:2169-9003
2169-9011
DOI:10.1029/2018JF004975