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Nature-based Simulation to Address Climate Change-Related Flooding. Preliminary Insights on a Small-Sized Italian City

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Computational Science and Its Applications – ICCSA 2021 (ICCSA 2021)

Abstract

Climate change impacts on cities are likely to require changes in urban adaptation planning. Despite the low degree of climate change manageability, the Nature-Based Solutions (NBS) are considered resilient measures that integrate the ecological dimension into spatial planning while playing a crucial role in addressing societal challenges and multiple benefits.

In urban planning, ecosystem models can be used to develop flood management strategies even if the limited experience with models and model output is a challenge for planners in thinking about addressing potential climate change impacts effectively. Consequently, this new challenge is based on the need for spatially explicit biophysical assessment related to NBS scenarios’ implementation.

This study considers the urban flood vulnerability assessment and how these vulnerabilities can be reduced through NBS simulation scenarios in a small-sized Italian coastal city of the Liguria Region. To quantify the amount of runoff during extreme rainfall events while identifying the greatest critical areas, the Urban Flood Risk Mitigation model (InVEST) integrated into a GIS environment have been employed. Furthermore, the biophysical assessment of NBS implementation has been supported by highlighting the crucial role of biodiversity type.

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Notes

  1. 1.

    https://ec.europa.eu/environment/water/flood_risk/better_options.html.

  2. 2.

    Available at https://naturalcapitalproject.stanford.edu/software/invest.

  3. 3.

    https://www.arpal.liguria.it/homepage/meteo/analisi-climatologiche/atlante-climatico-della-liguria.html.

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Correspondence to Carlotta Quagliolo .

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Quagliolo, C., Comino, E., Pezzoli, A. (2021). Nature-based Simulation to Address Climate Change-Related Flooding. Preliminary Insights on a Small-Sized Italian City. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12955. Springer, Cham. https://doi.org/10.1007/978-3-030-87007-2_39

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  • DOI: https://doi.org/10.1007/978-3-030-87007-2_39

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