Multi-data settlement prediction along a road section integrating InSAR and coastal subsurface information with data assimilation

Abstract

This paper presents a novel approach to examining the impact of soil settlement and its spatial distribution on infrastructure. The study focuses on a specific road section in the Friesland coastal plain in the north of the Netherlands, investigating how the Holocene coastal subsurface architecture influences settlement patterns. Our study underscores the importance of integrating multiple datasets, providing data at varying resolutions. The road segment traverses lithostratigraphical units, which include tidal channel and tidal flat deposits, overlaying an older tidal basin system and intercalated peat beds. Through data assimilation of a settlement model optimized with InSAR measurements, we have identified settlement heterogeneities that can be explained by combining high-resolution variations in lithology with gradual changes in lithostratigraphy. This was accomplished by utilizing a medium-resolution model (MRM) based on borehole descriptions and a high-resolution data (HRD) approach based on cone penetration tests along the road. The HRD method proved more effective in capturing abrupt changes in lithology between channel structures, while the MRM provided a continuous representation of the lithostratigraphic setting of the area. Our study demonstrates that subsurface heterogeneities have significant implications for subsidence along roads. Settlement rates increase from 2–4 mm/year towards 9 mm/year along the road section, resulting in a differential settlement of more than 5 mm/year over a distance of less than a kilometer. This is primarily attributed to variations in lithostratigraphy. Overall, this new innovative approach offers a practical and cost-effective solution for predicting subsidence due to settlement, eliminating the need for expensive laboratory tests. By integrating lithology and lithostratigraphy, more efficient road maintenance and management become possible.