4.7 Article

Investigating flood exposure induced socioeconomic risk and mitigation strategy under climate change and urbanization at a city scale

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JOURNAL OF CLEANER PRODUCTION
卷 387, 期 -, 页码 -

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ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2023.135929

关键词

Flood exposure; Climate change; Urbanization; Shared socioeconomic pathways; Green infrastructure; Chaohu city

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Investigating future flood exposure risk and associated mitigation strategies is vital for sustainable urban development. This study utilized hydrological modeling and future climate and urbanization scenarios to investigate the risk of flood exposure and the effectiveness of mitigation strategies at the city scale. The results showed that the current hydrological pattern in a highly urbanized and densely populated region in China caused a significant portion of the population and GDP to be exposed to flooding threats. Scenario analysis demonstrated that high-carbon emission scenarios increased population and GDP exposures to flood, while a green infrastructure strategy effectively decreased these exposures in low-carbon emission scenarios. Uncertainty analysis showed wide uncertainty ranges in future scenarios, and the green infrastructure strategy reduced the flood exposure uncertainty ranges. Spatial analysis indicated that population- and GDP-intensive regions were more vulnerable to flood exposure, but the effectiveness of the green infrastructure strategy was limited in these regions. The data from this study can assist in sustainable urban development in response to climate change and urbanization.
Investigating future flood exposure risk and associated mitigation strategies is vital for sustainable urban development. This study coupled hydrological modeling with future climate and urbanization scenarios from Representative Concentration Pathways and Shared Socioeconomic Pathways (SSP), to spatiotemporally investigate the risk of flood exposure and the effectiveness of mitigation strategy at the city scale. A highly urbanized (80% of built-up areas) and densely populated (7500 per km(2)) region in downtown Chaohu, China was selected as the study case. Results showed that the current hydrological pattern brought 4.64 x 10(6) m(3) of annual runoff and 292.00 l s(-1) of peak flow to the given area, thereby causing 41.03% of the population to be exposed to flooding threats and putting 51.17% of Gross Domestic Product (GDP) at risk. Scenario analysis demonstrated that population and GDP exposures to flood increased to at most 61.11 and 71.30% in high-carbon emission scenarios (SSP3-7.0/SSP5-8.5), respectively. The green infrastructure (GI) strategy captured at most 81.43% of runoff volume and 54.53% of peak flow, thereby decreasing population and GDP exposures to at least 18.38 and 33.04% in low-carbon emission scenarios (SSP1-2.6/SSP2-4.5), respectively. According to the uncertainty analysis, population and GDP exposures showed wide uncertainty ranges of 18.38-61.11 and 33.04-71.30% in future scenarios, and the GI strategy effectively decreased the flood exposure uncertainty ranges to 15.56-42.70 and 17.35-43.60%, respectively. In addition, the spatial analysis indicated that the population- and GDP-intensive regions were more vulnerable to flood exposure than other regions, while GI strategy in these regions showed limited effectiveness in mitigation of exposure risk. The data of this study could assist sustainable urban development in response to climate change and urbanization.

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