Growing incidents of structural damage and failures underscore the urgent need for more advanced Structural Health Monitoring (SHM) solutions. While Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) has revolutionised SHM by enabling automated, long-term, and large-scale displacement monitoring of structures using Persistent Scatterers (PSs), its applicability is often constrained by the unpredictable spatial distribution of PSs. Conventional suitability assessments that rely primarily on PS density fail to account for the underlying structural behaviours, limiting their reliability.

This paper introduces a novel structural-based inverse approach that uniquely integrates MT-InSAR characteristics with structural response modelling to overcome these limitations. Unlike existing approaches, the method explicitly evaluates whether observed surface displacements adequately represent a target damage mechanism by comparing outputs from a pseudo sensor with those from a virtual MT-InSAR sensor. If this condition is satisfied, it then determines the minimum required number and optimal spatial arrangement of ideal PSs using modified pivoted QR factorisation, where satellite-induced positional uncertainties are rigorously modelled through Radial Basis Function kernels.

The proposed method was validated on a quay wall in Amsterdam using Finite Element Method (FEM) simulations of three distinct damage mechanisms. Results demonstrate its unique capability to quantitatively assess displacement representativeness and to pinpoint ideal PSs for robust monitoring. Leveraging these insights, the method was further applied to evaluate MT-InSAR monitoring feasibility across Amsterdam’s historic centre, successfully identifying quay wall segments amenable to reliable observation. This work represents a significant advancement in MT-InSAR-based SHM, providing a more targeted and structurally informed approach for real-world infrastructure monitoring.

Large areas behind the historic quay walls and bridges in Amsterdam city center are prone to soil mobilization and cavity (sinkhole) formation due to intensified infrastructure developments and extreme groundwater level fluctuations caused by climate change. We carried out a geophysical survey to investigate a sinkhole formed under the Muntplein (Amsterdam, The Netherlands). The surface trace (hole) of the sinkhole was triggered by a heavy vehicle passing over the street which lies in the vicinity of a quay wall and behind the abutment of the Muntsluis bridge. The application of ground penetrating radar (GPR) and electric resistivity tomography (ERT) provided continuous data of the shallow subsurface which enabled the detection of the backfilled cavity, its southwest (SW) extension, the bridge abutment-to-soil transition, key utility lines and the presence of two potential targets for further investigation. A follow-up geotechnical assessment supported by hydrographic survey in the canal validated our findings and substantiated our first interpretation (i.e., sinkhole in development). The paper demonstrates the applicability of non-invasive electromagnetic (EM) methods to rapidly detect cavities in critical urban areas, and, thus, to de-risk climate-smart infrastructure developments.

The implementation of effective and sustainable Structural Health Monitoring (SHM) systems for the evaluation of infrastructure conditions is critical to address the deterioration and damage experienced by structures worldwide. Given the vast number of structures involved, resorting to traditional in-situ visual inspections and data gathering methods is becoming increasingly unfeasible. Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) has recently gained attention as a viable solution for long-term SHM. This remote sensing technique combines multiple satellite radar images to measure changes in the Earth’s surface over time. Unlike conventional techniques, MT-InSAR does not require in-situ installations and offers extensive coverage, enabling observations across diverse location and structures. However, the applicability of MT-InSAR monitoring depends on the relatively unpredictable distribution and location of permanent scatterers (PSs), which are influenced by surface characteristics and vegetation changes. Evaluating the reliability and capacity of MT-InSAR is therefore crucial to enhance its effectiveness in assessing the location and extent of structural damage. In this study, we present an effective approach to determine the optimal number and position of PSs for detecting different structural damage mechanisms. The approach is exemplified through a case study of a quay wall in Amsterdam, with data inputs simulated using the Finite Element Method. The proposed method has the potential to evaluate the feasibility of MT-InSAR for a broader range of scenarios, enabling to detect specific structural conditions.

The structural health of historic quay walls needs to be evaluated well in light of the new conditions they are subjected to. For that, information about their current subsurface structure and condition of their subsurface constructional elements, but also information about the surrounding subsurface structure is crucial. Such information can be supplied by seismic imaging and characterization. We show preliminary results from a high-resolution S-wave survey we performed at a historic quay wall in Overamstel, the Netherlands. We recorded data along four lines – two parallel and two perpendicular to the quay wall. We used a sledge-hammer and a beam as a source and 10-Hz horizontal-component geophones, both oriented in the crossline direction. We show that applying simple processing along the two parallel lines to obtain stacked sections already allowed extracting useful structural information of the subsurface.

An advection–diffusion model of fluvial processes was used to analyze the stratigraphic expression of avulsions in terminal river systems and understand their control on basin-fill architecture. The initial and boundary conditions of the model runs (i.e., catchment area, smoothed initial topographic surface, grain-size distribution and sediment supply rates) were extracted from the modern Rio Colorado dryland terminal river system in the Altiplano Basin (Bolivia). Water-discharge and sediment-load values were derived from global regression curves and the BQART equation, respectively. To evaluate the robustness of the simulations, the model was tested under increasing sediment-load scenarios ranging from 0.003 m³/s to 0.095 m³/s. Data-model comparison provided insights into the role of avulsions in the geomorphological evolution of terminal river systems. The observed stacking of sediments, as captured by geospatial and geochronological data from the Rio Colorado, is consistent with the high sediment-load scenarios, which start with a single-thread fluvial channel that in time radially expands over the floodplain by successive river avulsions on account of alluvial-ridge aggradation and channel-floor elevation above the surrounding floodplain. The model output shows a laterally extensive, convex-upwards lobate topography which is in agreement with the lateral and longitudinal geomorphology in the upper and lower coastal plain of the Rio Colorado. The simulated inter-avulsion period, which is the time period between two successive full (or stabilized) avulsions in the model, varies from 0.18 to 1.2 kyr and is consistent with the OSL-age determination in the Rio Colorado with inter-avulsion periods up to 1.28 ± 0.34 kyr.

Stratigraphic forward modelling (SFM) provides the means to produce geologically coherent and realistic models. In this paper, we demonstrate the possibility of matching lithological variability simulated with a basin-scale advection-diffusion SFM to a data-rich real-world setting, i.e. the Holocene Rhine-Meuse fluvio-deltaic system in the Netherlands. SFM model calibration to real-world data in general has proven non-trivial. This study focuses on a novel inversion process constrained by the top surface and the sand proportion observed at specific pseudo-wells in the study area. Goodness-of-fit expressed by a new fitness function gives the error calculated as the average of two calibration constraints. Computational efficiency was increased significantly by implementing a new optimization process in two hierarchical steps: a) optimization in terms of sediment load and discharge, which are the most influential parameters having the largest uncertainty and b) optimization with respect to the remaining uncertain parameters, these being sediment transport parameters. The calibration process described allows for the most optimal combination of achieving acceptable levels of goodness-of-fit, feasible runtimes and multiple (non-unique) solutions to obtain synthetic stratigraphic output best matching real-world datasets. By removing model realizations which are geologically unrealistic, calibrated SFM models provide a multiscale stratigraphic framework for reconstructing static models of reservoirs which are consistent with the palaeogeographic layout, basin-fill history and external drivers (e.g. sea level, sediment supply). The static reservoir models that are matched with highest certainty therefore contain the highest geological realism and may be used to improve deep subsurface reservoir or aquifer property prediction. The new methodology was applied to the well-established Holocene Rhine-Meuse dataset, which allows a rigorous testing of the optimization; the calibrated SFM allows investigation of controls of the Holocene development on the sedimentary system.

Multiscale simulation of fluvio-deltaic stratigraphy was used to quantify the elements of the geometry and architectural arrangement of sub-seismic-scale fluvial-to-shelf sedimentary segments. We conducted numerical experiments of fluvio-deltaic system evolution by simulating the accommodation-to-sediment-supply (A/S) cycles of varying wavelength and amplitude with the objective to produce synthetic 3-D stratigraphic records. Post-processing routines were developed in order to investigate delta lobe architecture in relation to channel-network evolution throughout A/S cycles, estimate net sediment accumulation rates in 3-D space, and extract chronostratigraphically constrained lithosomes (or chronosomes) to quantify large-scale connectivity, that is, the spatial distribution of high net-to-gross lithologies. Chronosomes formed under the conditions of channel-belt aggradation are separated by laterally continuous abandonment surfaces associated with major avulsions and delta-lobe switches. Chronosomes corresponding to periods in which sea level drops below the inherited shelf break, that is, the youngest portions of the late falling stage systems tract (FSST), form in the virtual absence of major avulsions, owing to the incision in their upstream parts, and thus display purely degradational architecture. Detailed investigation of chronosomes within the late FSST showed that their spatial continuity may be disrupted by higher-frequency A/S cycles to produce “stranded” sand-rich bodies encased in shales. Chronosomes formed during early and late falling stage (FSST) demonstrate the highest large-scale connectivity in their proximal and distal areas, respectively. Lower-amplitude base level changes, representative of greenhouse periods during which the shelf break is not exposed, increase the magnitude of delta-lobe switching and favour the development of system-wide abandonment surfaces, whose expression in real-world stratigraphy is likely to reflect the intertwined effects of high-frequency allogenic forcing and differential subsidence.

Process-based stratigraphic models provide attractive tools to simulate sedimentary system dynamics spanning a wide range of spatial and temporal scales and segments of the sediment routing system while allowing full access to the model responses, i.e. the spatial distribution of lithologies as a function of the intervening processes and environmental conditions at the time of deposition. Apart from improving our understanding regarding the evolution of sedimentary systems under pre-specified allogenic forcing mechanisms and intrinsic dynamics, process-based stratigraphic models can be used to improve basin-fill history reconstructions and increase the geological credibility of static reservoir models by integrating regional information to local-scale heterogeneities. The realism and predictive power of the model responses and geological model realizations may be quantitatively assessed by comparison with the geophysical/geological data available.