Landslide susceptibility modeling is widely used to support spatial planning and risk mitigation, butits reliability is strongly dependent on the completeness and quality of landslide inventories. In recent years, Interferometric Synthetic Aperture Radar (InSAR) has been proposed as a tool to augment these inventories by detecting surface deformation associated with slope instability. However, the conditions under which InSAR-derived deformation can be effectively integrated into susceptibility modeling remain unclear. This study investigates the feasibility and limitations of incorporating InSAR-derived surface deformation time series into landslide susceptibility modeling for the island of Ischia (Italy), a geomorphologically complex and landslide-prone environment. A traditional susceptibility model was first developed using established static controlling factors, including slope, lithology, soil thickness, terrain wetness index, land use, curvature, aspect, and rainfall. The model achieved satisfactory performance and identified slope as the dominant controlling factor, consistent with the expected behaviour of rainfall-induced landslides. To assess the contribution of InSAR, deformation time series derived from Sentinel-1 data (2019– 2025) were used to generate additional landslide samples based on a statistically defined detectability power threshold. These samples were then incorporated into the landslide inventory to produce an augmented susceptibility model. The analysis focused on comparing three scenarios: a traditional model, an InSAR-augmented model using slope-filtered deformation points, and an augmented model including all InSAR-derived points without additional geomorphological filtering. The results show that the integration of InSAR-derived landslides does not automatically improve model performance. When slope-based filtering is applied, the augmented model preserves the geomorphological consistency of the traditional model, with slope remaining the dominant controlling factor. However, when InSAR-derived points from low-slope areas are included, model performance decreases and land cover becomes the dominant predictor, indicating that the model is capturing non-landsliderelated deformation processes associated with urban areas and observation bias. These findings demonstrate that standard InSAR quality filtering is not sufficient to ensure that detected deformation corresponds to slope instability. The successful integration of InSAR into landslide susceptibility modeling requires the application of explicit geomorphological constraints, particularly slope-based filtering, to exclude deformation signals unrelated to landslide processes. InSAR should therefore be considered a complementary data source whose value depends on careful filtering and interpretation, rather than a direct replacement for traditional landslide inventories.

This research explores the feasibility of implementing ceramic microfiltration (CMF) treatment in Maputo, Mozambique, to reclaim wastewater for industrial reuse, addressing the city's pressing water scarcity challenges. As rapid urbanization increases Maputo's reliance on potable water for industrial and agricultural needs, this study evaluates reclaimed wastewater as a sustainable alternative to alleviate demand on the city's limited freshwater resources. Using a CMF pilot plant, the project tested wastewater from the recently upgraded Infulene Wastewater Treatment Plant (WWTP) to assess whether CMF treatment could achieve quality standards suitable for applications such as cooling, concrete production, car washes, agricultural irrigation, and municipal park irrigation. Furthermore, the opportunity of scalability was tested through a water balance, while relevant stakeholders were interviewed and costs estimated to complete the feasibility assessment.

Laboratory results indicated that CMF treatment effectively reduces turbidity, chemical oxygen demand (COD), and biological pollutants like E. coli and coliforms. However, dissolved particles and heavy metals were not removed, limiting its efficacy for high-specification uses. While the treated effluent met quality standards for lower-specification applications, such as local car washes and park irrigation, it did not reach the stricter requirements needed for cooling water or concrete production. This underscores a need for process optimization, particularly through coagulation, to expand CMF's application range.

To assess sustainable water availability, a water balance analysis of the Infulene WWTP considered seasonal flows and local agricultural demands. The findings suggest that although the current water supply is insufficient during dry months, full capacity utilization and improved sewer network connections in the future could support CMF-based water reuse consistently across seasons, with potential scalability for additional users.

Economic analysis compared CMF's capital and operational costs with revenue from reclaimed water sales, showing that while considerable initial investment is required, direct piping could potentially make CMF-treated water competitively priced against potable supplies under the condition of reaching maximum treatment capacity at a scaled up CMF plant. High costs associated with truck-based delivery, however, present a barrier to adoption for potential users. Stakeholder interest was strong across industrial users and developers, though contingent on achieving cost parity with the existing water network.

This study concludes that, while integrating CMF technology into Maputo's water management strategy offers promise, challenges remain in achieving quality standards for certain industrial applications and in lowering costs. Addressing these technical and economic barriers could open avenues for CMF's broader adoption, especially with future assessments that include alternative suppliers and configurations.