Climate change is expected to modify the timing and amount of precipitation in the future, increasing the demand for effective adaptation at the local scale, especially to mitigate the impacts of extreme events, expected to increase in frequency and magnitude. Green infrastructure (GI) can provide a crucial water regulating ecosystem service, helping communities to adapt to the increased stormwater runoff and associated flood risks expected from climate change. This paper presents a new planning tool that utilizes remote sensing and census data to model the supply and demand for urban flood reduction services through GI. A high-resolution urban digital model is used to distinguish between permeable and impermeable areas at fine (e.g. 25 cm) spatial scale. Flood reduction capacity was modeled using two indices: i) the amount of runoff reduced by existing GI, and ii) the runoff reduction coefficient. We also analyzed the flood reduction demand using a vulnerability index. The tool is demonstrated in a historical urban center of the Northern Italy, with different scenarios used to identify priority areas of intervention. The results show that the flood reduction capacity is unevenly distributed throughout the study area. Public and private surfaces contribute different amounts of runoff with different flood reduction potentials. In eight of nine urban study areas, private properties generate more runoff than public properties under the worst scenario conditions. The study identified two priority areas of intervention, based on their mismatch between supply and demand of GI's water regulating services.

Fine-scale analysis of urban flooding reduction from green infrastructure: An ecosystem services approach for the management of water flows

Gaglio Mattias
Secondo
;
Fano Elisa Anna
Penultimo
;
2018

Abstract

Climate change is expected to modify the timing and amount of precipitation in the future, increasing the demand for effective adaptation at the local scale, especially to mitigate the impacts of extreme events, expected to increase in frequency and magnitude. Green infrastructure (GI) can provide a crucial water regulating ecosystem service, helping communities to adapt to the increased stormwater runoff and associated flood risks expected from climate change. This paper presents a new planning tool that utilizes remote sensing and census data to model the supply and demand for urban flood reduction services through GI. A high-resolution urban digital model is used to distinguish between permeable and impermeable areas at fine (e.g. 25 cm) spatial scale. Flood reduction capacity was modeled using two indices: i) the amount of runoff reduced by existing GI, and ii) the runoff reduction coefficient. We also analyzed the flood reduction demand using a vulnerability index. The tool is demonstrated in a historical urban center of the Northern Italy, with different scenarios used to identify priority areas of intervention. The results show that the flood reduction capacity is unevenly distributed throughout the study area. Public and private surfaces contribute different amounts of runoff with different flood reduction potentials. In eight of nine urban study areas, private properties generate more runoff than public properties under the worst scenario conditions. The study identified two priority areas of intervention, based on their mismatch between supply and demand of GI's water regulating services.
2018
Maragno, Denis; Gaglio, Mattias; Robbi, Martina; Appiotti, Federica; Fano, Elisa Anna; Gissi, Elena
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2393752
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