When floods hit the road: Resilience to flood-related traffic disruption in the San Francisco Bay Area and beyond
When floods hit the road: Resilience to flood-related traffic disruption in the San Francisco Bay Area and beyond
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DOI：
10.1126/sciadv.aba2423
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发表时间：
2020-08-01
期刊：
影响因子：
13.6
通讯作者：
Suckale, Jenny
中科院分区：
文献类型：
--
作者：
Kasmalkar, Indraneel G.;Serafin, Katherine A.;Suckale, Jenny
随着海平面上升，低洼沿海地区的城市交通网络面临着越来越大的洪水中断风险。被洪水淹没的道路封闭导致员工缺勤和延误，对社区造成连锁影响。我们将交通模型与洪水地图相结合，洪水地图代表了风暴潮、潮汐、季节周期、由大规模气候变化（如厄尔尼诺南方涛动）和海平面上升驱动的年际异常的潜在组合。在识别被淹没的道路时，我们建议纠正模型集成产生的潜在偏差。我们对旧金山湾区的调查结果显示，员工缺勤仅限于洪水区域内的家庭和工作场所，而延误情况则蔓延到内陆地区。备用道路有限的社区无论距离洪水区域有多远，都会经历长时间的延误。我们表明，衡量道路网络密度的指标范围比洪水暴露更能代表延误。
As sea level rises, urban traffic networks in low-lying coastal areas face increasing risks of flood disruptions. Closure of flooded roads causes employee absences and delays, creating cascading impacts to communities. We integrate a traffic model with flood maps that represent potential combinations of storm surges, tides, seasonal cycles, interannual anomalies driven by large-scale climate variability such as the El Nino Southern Oscillation, and sea level rise. When identifying inundated roads, we propose corrections for potential biases arising from model integration. Our results for the San Francisco Bay Area show that employee absences are limited to the homes and workplaces within the areas of inundation, while delays propagate far inland. Communities with limited availability of alternate roads experience long delays irrespective of their proximity to the areas of inundation. We show that metric reach, a measure of road network density, is a better proxy for delays than flood exposure.