During the reporting period, substantial progress was achieved towards the first two scientific objectives of DEEP.
For Objective 1, a quantitative and reproducible workflow was developed for the identification and characterisation of homogenite–turbidite deposits. A complete XCT processing workflow was implemented using Fiji, including image pre-processing, automated extraction of CT-number profiles, normalisation and statistical analysis. The approach was tested on representative core sections containing homogenites, turbidites, hemipelagic sediments and mass-transport deposits. At a larger scale, 841 XCT scans from 58 sediment cores, corresponding to approximately 832 m of sediment and 881 core sections, were processed and organised into standardised high-resolution 3D datasets and visualisation plates. This provides a consistent basis for large-scale comparative analysis and future automation.
High-resolution micro-XCT analyses were also initiated on 12 core sections from the Japan Trench, representing approximately 3.42 m of sediment. These analyses are being used to investigate grain-size distributions, three-dimensional sedimentary structures and depositional interfaces at a much finer scale than conventional XCT imaging. Additional training was undertaken to address the complexity of the datasets and optimise their analysis. The project also integrated complementary physical-property and geochemical observations, including MSCL, SCOPIX and XRF data, strengthening the multi-proxy characterisation of the sedimentary record.
For Objective 2, chronological information from radiocarbon dating, 210Pb, paleomagnetism and tephrochronology was compiled and integrated with sedimentological observations to establish a robust chronostratigraphic framework for the Japan Trench cores. A key result was the identification of a sedimentary sequence interpreted as being associated with the historically documented 869 CE Jōgan megathrust earthquake. This deposit is currently being investigated using high-resolution sedimentology, grain-size extraction from micro-XCT, three-dimensional reconstruction and integration with XCT and physical-property data. IODP Expedition 405 material and associated SCOPIX and XRF observations were also incorporated to support targeted analyses.
Preparatory work for Objective 3 was initiated through the standardisation of XCT-derived parameters and the development of reproducible workflows for large datasets. Initial machine-learning approaches for automated lithofacies classification were explored. These activities provide the methodological foundations required for the subsequent integration of offshore geological records into a broader database for paleoseismic and tsunami hazard assessment.
Overall, the project has established the main methodological basis for quantitative HmTu characterisation, generated a substantial standardised XCT dataset, developed a multi-proxy analytical framework and identified a key geological record linked to a known historical megathrust earthquake.