LIDAR DERIVED SALT MARSH TOPOGRAPHY AND BIOMASS: DEFINING ACCURACY AND SPATIAL PATTERNS OF UNCERTAINTY

Floods harm crops very differently depending on when they happen: the same flooding can ruin a field at flowering but barely affect it after harvest. Risk studies usually overlook this timing. We built a method that simulates realistic rainstorms month by month, follows the water across the landscape, and links the flooding to how sensitive each crop is then. Timing changes expected yearly losses considerably, helping farmers and planners protect the right places at the right time.

Sea level records are often too short. The traditional asymptotic extreme value analysis fails to produce accurate results with short records. By leveraging the non-asymptotic Metastatistical Extreme Value Distribution via the integration of two novel independent event selection methodologies, along with a robust cross-validation procedure, we found that our methodology can accurately estimate the likelihood of long return period extreme sea level events in data-scarce settings.

This study aims at inspecting organic matter dynamics affecting the survival and carbon sink potential of salt marshes, which are valuable yet endangered wetland environments. Measuring the organic matter content in marsh soils and its relationship with environmental variables, we observed that the organic matter accumulation varies at different scales, and it is driven by the interplay between sediment supply and vegetation, which are affected, in turn, by marine and fluvial influences.

Sediment erosion induced by wind waves is one of the main drivers of the morphological evolution of shallow tidal environments. However, a reliable description of erosion events for the long-term morphodynamic modelling of tidal systems is still lacking. By statistically characterizing sediment erosion dynamics in the Venice Lagoon over the last 4 centuries, we set up a novel framework for a synthetic, yet reliable, description of erosion events in tidal systems.