Structural Health Monitoring under Climate Change

Structural Health Monitoring has just published our special issue on the impact of climate change on the structural health monitoring of civil infrastructure.

Figueiredo E, Moldovan I, Santos LO. Impact of climate change on the structural health monitoring of civil infrastructure. Structural Health Monitoring. 2025;24(4):2250-2251. doi:10.1177/14759217251351724

Infrastructure plays a crucial role in modern societies, regardless of culture, geographical location, or economic development. The safest, most economical, and most resilient infrastructure is the one that is well managed and maintained. Structural health monitoring (SHM) has been proposed to support these tasks, but it still faces several challenges in field implementation. The effects of operational and environmental variability have been identified as one of the biggest challenges in transitioning SHM from research to practice.

Recently, climate change has been posed as one of the greatest concerns for the health of infrastructure, especially bridges, buildings, dams, railways, and roads. Although the uncertainty associated with the magnitude of the change is large, the fact that our climate is changing is unequivocal. As a result, making infrastructure resilient to climate change is a priority for the authorities.

The health and serviceability of infrastructure are assumed to be compromised by the following projected changes: (1) an increase of the frequency of heavy precipitation events, which may cause flooding and scouring; (2) higher temperatures and more frequent heat waves, which are expected in the years ahead and may cause additional stresses and deformations; (3) increased levels of atmospheric CO2 concentration and relative humidity, which may trigger concrete carbonation and increase corrosion; and (4) sea-level rise, which may result in the relocation of infrastructure.

Preliminary studies suggest that climate change will significantly affect our infrastructure, its monitoring systems, and the features used to monitor its response over time. Therefore, what happens if the climate changes over time? Will it significantly affect the outcome of SHM? Will the reference dataset used for the training of algorithms become outdated? Are machine learning algorithms robust enough to deal with climate change?

This special issue (SI) intended to bring together publications involving studies on the impacts of climate change on the SHM of infrastructure. Five publications have been incorporated into this SI, and their contributions are summarized as follows:

• Figueiredo et al. (2024): Climate change–driven temperature shifts can reduce the reliability of ML-based SHM systems, causing misclassification of damage. Highlights the need for climate-adaptive models. 
• Möller et al. (2025): Grey-box models using Gaussian process regression, enriched with physical knowledge, improve SHM resilience under sparse or changing climate conditions. 
• Quqa et al. (2024): Proposes scalable SHM via satellite InSAR, harmonizing displacement and environmental data to detect climate-induced bridge anomalies without dense sensors. 
• Quqa et al. (2025): Reviews SHM under climate stress, advocating regional-scale, multi-source strategies (indirect, satellite, population-based) and knowledge transfer to enhance cost-effective climate resilience. 
• Rincon et al. (2025): Develops methods to impute missing SHM sensor data (resistivity, temperature) using hybrid AI/statistical techniques, preserving data integrity for climate-driven corrosion monitoring.