Multi-scenario analysis in the Apulia shoreline: A multi-tiers analytical framework for the combined evaluation and management of coastal erosion and water quality risks

Ongoing climate change is causing threats to coastal areas, according to scenarios of Intergovernmental Panel on Climate Change (IPCC). The coastal areas are becoming highly exposed to erosion as a direct consequence of natural and anthropogenic processes that occur at different spatial-temporal scales. Against this interplay, coastal managers are calling for integrated tools supporting a multi-scenario evaluation of risks arising from natural and anthropogenic stress. A multi-tier analytical framework, exploiting the openly available Earth Observation databases, was developed, allowing the combination of remote sensing, GIS and Bayesian Network to evaluate the probability and uncertainty of coastal erosion risks and connected water quality variation, against what-if scenarios, representing different management measures (i.e., Nature-Based Solution) and climate change impacts (e.g., higher incident waves due to increased storminess). Based on the available data for the Municipality of Ugento (Italy), the designed framework was applied over the 2009-2018 timeframe, allowing to capture local-scale shoreline erosion dynamics and driving forces. Results from scenario analysis revealed, to a minor extent, a nexus between oceanographic drivers, shoreline evolution, and water quality changes, with increasing probability of high erosion/accretion and higher turbidity under the simulated rising maximum significant wave height. However, the implementation of Nature-Based Solutions (i.e., circular approach exploiting beached Posidonia oceanica leaves) resulted in significant positive effects, stabilizing the shoreline by reducing high erosion and accretion rates. Despite data constraints, outcomes of the performed assessment could represent valuable information to drive adaptive policy pathways in the context of coastal management along the Ugento shoreline.