Abstract
Climate change impacts urban areas with greater frequency and exposes continental cities located on floodplains to extreme cloudbursts events. This scenario requires developing specific flooding vulnerability mitigation strategies that improve local knowledge of flood-prone areas at the urban scale and supersede the traditional hazard approach based on the classification of riverine buffers. Moreover, decision-makers need to adopt performance-based strategies for contrasting climate changes and increasing the resilience of the system. This research develops the recent Flooding Risk Mitigation model of InVEST (Integrated Evaluation of Ecosystem Services and Trade-off), where cloudburst vulnerability results from the soil’s hydrological conductivity. It is based on the assumption that during cloudburst events, all saturated soils have the potential for flooding, regardless of the distance to rivers or channels, causing damage and, in the worst cases, victims. The model’s output gives the run-off retention index evaluated in the catchment area of Turin (Italy) and its neighborhoods. We evaluated the outcome to gain specific insight into potential land use adaptation strategies. The index is the first experimental biophysical assessment developed in this area, and it could prove useful in the revision process of the general town plan underway.
Highlights
The spatial knowledge of local conditions obtained using advanced digital technologies and modelling scenarios is one of the most debated and discussed approaches to preparing and adapting urban systems to deal with future challenges [1,2]
This study aims to apply a similar methodology in an Italian context, while modelling with Geographic Information System (GIS)-based software the spatial distribution of the run-off, and to understand where and how nature-based solutions can contribute to adapt the system towards a greener and healthier environment
We propose a selection of Nature-Based Solutions (NBS) to be implemented through the Turin general town plan, based on the flooding vulnerability assessment as a framework to set the capacity to reduce a specific degree of vulnerability
Summary
The spatial knowledge of local conditions obtained using advanced digital technologies and modelling scenarios is one of the most debated and discussed approaches to preparing and adapting urban systems to deal with future challenges [1,2]. Despite the technological and social predictive capacity enabling us to understand where and how new phenomena will occur, it is certain that the traditional timescale, occurrence, and intensity of extreme events have changed and will continue to do so rapidly in the few decades, according to the most recent studies [6,7]. Considering that all cities can be potentially affected by extreme events, the vulnerability assessment includes an entire catchment, and how and where the catchment is prone to be impacted by certain circumstances (with a certain degree of intensity and with a predicted return time), as assumed by the traditional risk diagnosis.
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