The City of Amsterdam is responsible for the maintenance of 600 km of historic quay walls, most of which are over 100 years old while others are 300 years old and are experiencing stability and degradation problems. A lack of knowledge about the as-built information and the current conditions of the retaining structures and their foundation systems exists, and very limited guidelines for the assessment of quay walls are available. Predicting the time when the quay walls are no longer safe is a key challenge in their end-of-life assessment. For this purpose, monitoring of the quay walls via conventional techniques (e.g., in situ surveys, topographic levelling and tachymetry) combined with satellite Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) data provides updated information on the displacements affecting the retaining structures and/or their foundations. This paper develops a multiscale methodology, consisting of three phases, that allow (1) the prioritization of the most exposed retaining structures (quay walls) at the municipal scale, (2) the retrieval of empirical relationships between different damage/movement indicators and quantitative displacement descriptors obtained via in situ surveys and terrestrial monitoring data, and (3) the identification of the most probable collapse mechanism by jointly analyzing the wall crack patterns and monitoring data. The results show that this approach could play a fundamental role to set up sustainable risk mitigation strategies at the municipal scale.

This study presents a novel framework in which numerical modelling contributes to the performance of district-scale, subsidence-induced damage assessment in cities where ground settlements affect entire quarters. Therein, the implementation of expeditious procedures offers geotechnical engineers the possibility of contributing beyond the typical site scale. For this purpose, several “typified” hydro-geomechanical-loading (HGL) models, which represent (simplified) scenarios of masonry buildings undergoing settlements, were set up to account for different predisposing or triggering factors (i.e., soil heterogeneity, loading conditions, and groundwater variations) of settlement occurrence in built-up areas. These models exploit multi-source, wide-area input datasets encompassing the hydro-mechanical properties of geomaterials, in situ investigations and measurements (e.g., groundwater levels in wells), and innovative remote sensing data (i.e., DInSAR techniques). With reference to a district in Rotterdam City (the Netherlands), which was built on “soft soils”, the numerical simulations of different scenarios (i) provide an overview of the comparative role of predisposing or triggering factors on settlement occurrence and (ii) allow assessments of the expected induced damage to masonry buildings over 30 years with the exploitation of fragility curves. Considering the widespread diffusion of such geohazards, the proposed approach could help prioritise (rather expensive) maintenance work to the built heritage within sustainable strategies for subsidence risk mitigation.

The paper presents a probabilistic analysis aimed at identifying the most appropriate subsidence related intensity (SRI) parameter (e.g., differential settlement, relative rotation, deflection ratio) that can be used to forecast the severity level of building damage at municipal scale through the generation of empirical fragility and vulnerability curves. The analysis refers to a rich sample of more than seven hundred monitored (by remote sensing techniques) and surveyed masonry buildings – mainly resting with their (shallow or piled) foundations on highly compressible fine-grained “soft soils” – affected by settlements in four urban areas in The Netherlands. The achieved outcomes, once further calibrated and validated, could allow for an improvement of existing geotechnical damage criteria for buildings as well as help local authorities in charge of the management/protection of subsiding urban areas to plan adequate foundation repairing/replacing measures before damage reaches intolerable severity levels.