Predicting where floating plastic concentrates within the Great Pacific Garbage Patch is difficult because operational circulation models resolve the broad accumulation region, but not necessarily the smaller flow structures that form local hotspots. Reduced-order two-dimensional models offer an attractive way to reach finer horizontal resolution at lower computational cost, but their usefulness depends on whether they correctly retain the near-surface dynamics that control particle clustering. This thesis assesses under which dynamical conditions, and to what extent, a high-resolution 2D MITgcm framework can reproduce the surface-flow and surface-particle clustering statistics of matched 3D MITgcm benchmark simulations in a semi-idealized GPGP setting. The comparison combines Eulerian diagnostics of vorticity, strain, divergence, spectral content and submesoscale motion with Lagrangian particle-clustering metrics based on Voronoï tessellations. The results show that the 2D model can retain part of the broad mesoscale organization and surface-vorticity structure, especially under weaker energetic conditions. However, it does not reliably reproduce the connected high-strain structures, high-strain-high-vorticity asymmetry and compressive surface organization present in the 3D benchmarks. These differences limit its ability to reproduce finite-time particle clustering and local concentration extremes. The unaugmented 2D framework is therefore more defensible for qualitative broad-transport characterisation than for quantitative hotspot prediction. Future hotspot-oriented use should focus on controlled augmentation of the particle-advection kernel, using proxies for persistent filamentary attraction and unresolved surface convergence. ... Read more

High-altitude páramo ecosystems in the Ecuadorian Andes, which serve a vital function in controlling the local water cycle, conserving biodiversity and securing the livelihoods of the inhabitants, are increasingly threatened. Climate variability, natural disasters and the growing pressure on natural resources due to extractive land use are the main driers. This study assesses the future environmental and social risks in the South Ecuadorian páramo surrounding Cuenca using a multidisciplinary approach. It focuses on hydrological change, slope instability, water quality and stakeholder conflict. Long-term in-situ observations made at the Zhurucay and Quinuas ecohydrological observatories are complemented by satellite and reanalysis data. We analyse multi-year trends in temperature, precipitation, soil moisture and solar radiation. Remote sensing data are calibrated and validated against ground measurements in order to make them applicable to data-scarce areas. This work also uses trend analysis and forecasting of time-series to identify the emerging hydro-meteorological patterns and the synthetic rainfall scenarios and spatial data sets to assess the slope instability under changed conditions. Additionally, water-quality risks related to changed runoff dynamics and potential mining activities are assessed. The study also includes an analysis of stakeholders of the mining Loma Larga project in order to examine how the differences in power, interests and perceived risks contribute to social tensions around water security and land use. The results show an increasing hydro-meteorological variability which may worsen the landslide risk and challenge the buffer capacities of páramo soils, while mining-related disturbances pose an additional threat to the water quality downstream and to the governance. This work integrates the physical science, remote sensing and social analysis in order to provide a comprehensive framework for understanding the coupled human-environment risks in the páramo systems. The finding may help policymakers navigate these trade-offs to support informed decision-making and ecosystem-based approaches to hazard mitigation in fragile high-mountain landscapes.
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