Assessing the viscous compression parameter for land subsidence modelling from material characteristics

Abstract

Compaction of soft subsurface layers occurs through different mechanisms, namely con- solidation, viscous compression, autocompaction, and shrinkage. Viscous compression is a key long-term process often the most significant component of compaction over long time periods. The rate of viscous compression over time is defined by the viscous compression parameter (Cα), which describes the amount of strain per logarithmic unit of time with constant effective stress. Overall compressibility of different material can often be linked to their material characteristics, yet for viscous compression this is still problematic. Understanding the relationship between material characteristics and Cα is essential for improving compaction predictions in soft subsurface layers such as clay and peat. This study investigates how Cα varies with subsurface material characteristics and explores its predictability based on specific material characteristic values. An extensive dataset of one-dimensional compression tests on Holocene peat and clay samples from the Rhine-Meuse delta and coastal zone in the Netherlands was analysed. Using principal component and clustering analyses, four distinct lithological classes were identified and labelled based on organic fraction: Clay, Clayey peat, fibrous Peat & decomposed Peat. All four lithological classes show increasing median sample Cα values with decreasing bulk densities and increasing water content and void ratio, with Cα val- ues ranging from 0.0074 in the ‘Clay’ material type to 0.0293–0.0384 in the two ‘Peat’ ma- terial classes. Compared to currently applied traditional lithological classifications and default model values in the Netherlands, the material type-specific Cα values provide a more accurate and data-driven alternative. Regression analysis using the full dataset, with water content and dry bulk density as the predictors, yielded a better prediction of Cα (R² = 0.61) than for regressions per material type. Due to large variability within the peaty material types, upper and lower Cα bounds (0.02–0.06) are recommended in practi- cal applications for ‘Clayey Peat’ and ‘Peat’ subsurface layers, as these values are consis- tently observed across the full range of water content and dry bulk density within these clusters. While the Cα values for ‘Clay’ are similar to standard values (0.0035–0.0123), Cα values for ‘Clayey Peat’ and ‘Peat’ are up to three times higher than the standard values, which would result in twice or thrice the amount of viscous compression over the same time period. Finally, we emphasise the need for adaptable Cα values in models to reflect evolving material characteristics over time, driven by decomposition.