Development of a combined environmental and socio-economic costal vulnerability index: assessing vulnerability to inundation scenarios in the Italian coast

Abstract

Rising sea levels and extreme events related to climate change are causing serious threats to coastal areas, affecting both natural and human systems. Moreover, there is growing evidence that socio-economic dynamics (e.g. unplanned urbanization, land use and demographic changes) would increase coastal flood risk in the next decades. In this setting, coastal zones of the Mediterranean region represent highly vulnerable areas to climate-related impacts, as they are characterized by gentle slope environments, especially prone to be inundated by storm surge flooding events and rising sea level. In particular, when considering the geo-physical and morphological features of the Mediterranean shorelines as a whole, the Italian coastal area appears to be remarkably vulnerable to potential risks arising from future climate change scenarios due to its low lying and retreating shorelines, often lacking protection to erosion or storm surge events. Moreover, Italian coastal areas usually result highly populated and occupied by economically valuable assets, thus exposing people, infrastructures and businesses to potential climate-related damages. Understanding how natural and human-induced drivers will contribute together to rise the vulnerability and risks in coastal areas is of paramount importance for mainstreaming effective climate adaptation and risk reduction policies into coastal zone management. Moving forward traditional approaches for coastal vulnerability appraisal, an advanced Coastal Vulnerability Index, integrating a composite set of physical, environmental and socio-economic indicators (hereafter combined-CVI), is proposed in this Thesis in order to rank Italian coastal provinces according to their relative vulnerability to extreme sea level scenarios. In particular, hazard-prone areas potentially inundated by sea level rise and extreme water levels (under the RCP8.5 climate scenario) were combined with indicators of geomorphic vulnerability (e.g. elevation, distance from coastline, shoreline evolution trend) and adaptive capacity (e.g. sensible segments of the population, GDP, land use patterns). According to the temporal resolution of the available data, the methodology was applied by considering two different timeframe scenarios: a baseline representing current climate and land use condition, and a future scenario for the 2050, integrating both climate projections and data simulating potential evolution of the environmental and socio-economic systems. Results from the application of the combined-CVI in the Italian coast case study, including GIS-based vulnerability maps and related statistics, showed that most vulnerable provinces are located along the North Adriatic coast, the Gargano area and in the Southern part of Italy, due to the very high vulnerability score assumed by climate-related indicators, in both baseline and future scenario. Moreover, the number of provinces assuming higher vulnerability score is expected to increase in the future due to the worsening of climatic conditions, as well as the rising vulnerability linked with changes in the environmental and socio-economic conditions (e.g. land use variations and increase of the elderly population). Despite constraints posed by data availability, the resulting outputs of the performed analysis represent a useful screening tool about potential impacts induced by climate change and sea-level rise scenarios in the area of concern. Specifically, by providing a relative ranking of most vulnerable coastal provinces, they can be used by coastal managers and environmental planners to identify regions where inundation risk may be relatively higher, considering both environmental and socio-economic features, as well as to draw some considerations about the potential measures required to increase the resilience of coastal communities to sea-level rise and storm surge flooding scenarios, undertaking a sustainable adaptation pathway.