Incorporating Advanced Imaging Techniques for Climate-Resilient Geotechnical Asset Management

Geotechnical asset management (GAM) is in the early stages of adoption within transportation agencies, especially in Mississippi (MS). Geotechnical assets in central Mississippi are vulnerable to excessive deformation due to the high volume changing Yazoo clay, further impacted by the high amount of rainfall and seasonal variations. In a changing climate, high-intensity rainfall events add excessive loads on the geotechnical and transportation infrastructure assets causing catastrophic failures. Therefore a GAM program that addresses resiliency and climate adaptiveness is much needed. Infrastructure climate resilient design is geared toward recovering quickly from shocks from adverse effects due to natural hazards fueled by ever-increasing significant climate events. Geotechnical infrastructure assets should be built and maintained such that they are not only resilient but also adaptive to evolving climatological conditions. Highway authorities have attempted to incorporate resilience into their asset management programs in terms of uninterrupted performance under shifting conditions. However, there is a need to identify the damage and loss metrics for geotechnical assets and include them in the GAM. Furthermore, evaluation of climate-resilient geotechnical assets requires a precise examination of the effects of new extreme patterns on short- and long-term behavior. This is particularly accurate for geotechnical assets such as highway slopes built on high-volume changing clay whose performance and strength are impacted by long-term and short-term precipitation and temperature fluctuation. Without proper monitoring, the geotechnical assets are susceptible to failures causing significant social and economic impact. Integrating technologies to implement advanced monitoring and assessment techniques are much needed for a climate-resilient GAM. To this end, this study focuses on incorporating advanced imaging technologies such as electrical resistivity imaging (ERI) and uncrewed aerial vehicles (UAVs) with optical and thermal imaging sensors into geotechnical asset performance assessment. Furthermore, this study presents a methodology for using advanced imaging technologies in implementing a decision support structure to test and investigate the resilience and adaptiveness of geotechnical assets such as highway slopes in central Mississippi. The findings will benefit the decision-makers to implement robust geotechnical asset management solutions in light of the increased intensity and frequency of significant climate events.