Spatial heterogeneity of controlling factors’ impact on urban pluvial flooding in Cincinnati, US
Applied Geography, ISSN: 0143-6228, Vol: 125, Page: 102362
2020
- 14Citations
- 48Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Urban pluvial flooding has become a common threat for urban areas. Intensified rainfall, increasing imperviousness, and insufficient drainage capacity contribute to the increase of pluvial flood risk. The strategy of risk mitigation relies on the understanding of these controlling factors of urban pluvial flooding. However, spatial heterogeneity of the impacts of controlling factors has received limited attention. This study analyzes how topography, rainfall, impervious surfaces affect urban pluvial flooding and how the effects vary in space. A case study in the city of Cincinnati, US based on four storm events in recent years is conducted. The impact of topography is measured by a depression-based empirical parameter, Topographic Control Index (TCI), which is generated based on depression ponding volume, contributing area, and upstream slope. Rainfall depth estimated from kriging interpolation method is used to measure how the rainfall affect the urban pluvial flooding. The impervious area ratio of the contributing area of each depression as well as that of observed flooded locations are calculated to analyze the influence of impervious area. The results showed that TCI value and rainfall intensity are spatially correlated with the presence of flooded locations, and flooded locations can be classified into two types: rainfall control or topography control. The imperviousness of land surface does not show a significant correlation with pluvial flood due to the relatively small spatial variation of impervious area in a well-developed city. The framework in this study could identify the spatial distribution of dominant controlling factors for pluvial flooding, which is critical for the effective planning of mitigation measures.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0143622820304094; http://dx.doi.org/10.1016/j.apgeog.2020.102362; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85095765760&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0143622820304094; https://api.elsevier.com/content/article/PII:S0143622820304094?httpAccept=text/xml; https://api.elsevier.com/content/article/PII:S0143622820304094?httpAccept=text/plain; https://dul.usage.elsevier.com/doi/; https://dx.doi.org/10.1016/j.apgeog.2020.102362
Elsevier BV
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know