The first step in this project was to develop a probabilistic framework for seabed soil behavior type classification from PFFP measurements. This included tasks such as the assembly of the database from existing and newly collected data, the identification of soil behavior type classes relevant to UXO risk assessment problems, and correlation of PFFP measurements to the identified soil behavior type classes. Secondly, relationships between the following processes and properties and the soil behavior type classes were investigated: benthic biogenic activity, geoacoustic properties (low- and high-frequency), sediment erodibility, and seabed liquefaction from ocean waves. This was accomplished through dedicated field data collection efforts with co-located PFFP deployments, geotechnical soil classification from laboratory testing of high-quality sediment cores, identification and quantification of benthic activity through infauna assessment from sediment cores and in situ measurements, side-scan sonar and compressed high-density radiated pulse (CHIRP) sonar surveying, and erosion testing of sediment cores using a Gust microcosm erosion chamber. Seabed liquefaction was assessed based on soil type classification and previous observations from the literature. Finally, initial pathways were identified to implement the soil behavior type classification from PFFP in UXO risk assessment tools.

The key findings of this project include:

1. A novel probabilistic framework for rapid seabed classification and uncertainty quantification from PFFP for UXO risk assessment and other applications.
2. Methods to estimate geotechnical parameters and soil class directly from side scan sonar surveys and from combined CHIRP and PFFP surveys.
3. A new method to estimate critical shear stress for initiation of sediment transport from PFFP measurements or soil behavior type class.
4. A probabilistic framework to spatially assess the risk of ocean-wave driven seabed liquefaction from limited environmental parameters and PFFP data.
5. Initial guidance how to use those methods and frameworks for UXO risk assessment.

The research resulted in successful development of a simplified and probabilistic seabed soil classification framework from rapid PFFP measurements that provides a seabed sediment classification that includes measures of uncertainty in the assignment of site classes. It was demonstrated that the classification can be integrated with geoacoustic seabed surveying and provides guidance on erodibility and liquefaction risk. Infauna were found to have an impact on seabed surface sediments on the scale of the penetrometer or UXO. However, effects are complicated by spatial variability and temporal disconnects. Generally, results suggested that sediment weakening on the scale relevant for UXO from infauna is more likely than strengthening although it is acknowledged that some organisms strengthen sediments in their direct vicinity through compacting and increased cohesion. Finally, a step-wise approach is suggested for integrating geotechnical seabed classifications in UXO risk assessment tools to (i) optimize data collection efforts and (ii) decrease and quantify uncertainty.

Insights from this work have the potential to reduce data collection costs and uncertainty from seabed effects for UXO site management. The resulting approach offers pathways of interpolation and probabilistic methods to handle data gaps in a structured and informative way. Emerging machine learning and probabilistic tools will likely have the potential to advance this approach further. Next steps should explore the implementation of the suggested strategies and framework at UXO sites and in collaboration with UXO testbed or site managers. (Project Completion - 2026)