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| DOI | 10.1007/s11069-020-04427-5 |
| Estimating impacts of recurring flooding on roadway networks: a Norfolk, Virginia case study | |
| Praharaj S.; Chen T.D.; Zahura F.T.; Behl M.; Goodall J.L. | |
| 发表日期 | 2021 |
| ISSN | 0921030X |
| 起始页码 | 2363 |
| 结束页码 | 2387 |
| 卷号 | 107期号:3 |
| 英文摘要 | Climate change and sea level rise have increased the frequency and severity of flooding events in coastal communities. This study quantifies transportation impacts of recurring flooding using crowdsourced traffic and flood incident data. Agency-provided continuous count station traffic volume data at 12 locations is supplemented by crowd-sourced traffic data from location-based apps in Norfolk, Virginia, to assess the impacts of recurrent flooding on traffic flow. A random forest data predictive model utilizing roadway features, traffic flow characteristics, and hydrological data as inputs scales the spatial extent of traffic volume data from 12 to 7736 roadway segments. Modeling results suggest that between January 2017 and August 2018, City of Norfolk reported flood events reduced 24 h citywide vehicle-hours of travel (VHT) by 3%, on average. To examine the temporal and spatial variation of impacts, crowdsourced flood incident reports collected by navigation app Waze between August 2017 and August 2018 were also analyzed. Modeling results at the local scale show that on weekday afternoon and evening periods, flood-impacted areas experience a statistically significant 7% reduction in VHT and 12% reduction in vehicle-miles traveled, on average. These impacts vary across roadway types, with substantial decline in traffic volumes on freeways, while principal arterials experience increased traffic volumes during flood periods. Results suggest that analyzing recurring flooding at the local scale is more prudent as the impact is temporally and spatially heterogeneous. Furthermore, countermeasures to mitigate impacts require a dynamic strategy that can adapt to conditions across various time periods and at specific locations. © 2021, Springer Nature B.V. |
| 关键词 | Crowd-sourced dataData predictive modelImpact analysisRecurring flooding |
| 英文关键词 | crowdsourcing; flood; flooding; modeling; road traffic; road transport; Norfolk [Virginia]; United States; Virginia; Virginia |
| 语种 | 英语 |
| 来源期刊 | Natural Hazards
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/206499 |
| 作者单位 | Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA, United States; Department of Computer Science, University of Virginia, Charlottesville, VA, United States |
| 推荐引用方式 GB/T 7714 | Praharaj S.,Chen T.D.,Zahura F.T.,et al. Estimating impacts of recurring flooding on roadway networks: a Norfolk, Virginia case study[J],2021,107(3). |
| APA | Praharaj S.,Chen T.D.,Zahura F.T.,Behl M.,&Goodall J.L..(2021).Estimating impacts of recurring flooding on roadway networks: a Norfolk, Virginia case study.Natural Hazards,107(3). |
| MLA | Praharaj S.,et al."Estimating impacts of recurring flooding on roadway networks: a Norfolk, Virginia case study".Natural Hazards 107.3(2021). |
| 条目包含的文件 | 条目无相关文件。 | |||||
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