This article analyzes the spatio-temporal effect of the 2013 floods on freight traffic in Germany by using automatic traffic counter data. The methodology uses a proven time-series outlier detection and identification technique to endogenously determine if a counter was affected during the flood and estimate the magnitude and duration of the change in the number of vehicles passing through it. This is the first paper able to quantify climate-related variations in traffic across all the counters of a national network. Results show variations on 10% of all counters and 23% of all main roads. Results allow us to trace the configuration of disrupted and detour routes, recovery times, and the total effect on the network. Our findings serve as an input to other studies on the impact of exogenous events on the transport system and contribute towards the formulation of public policies to improve road resilience.

本文使用自动交通计数器数据分析了2013年洪水对德国货运的时空影响。该方法使用经过验证的时间序列离群值检测和识别技术来内生地确定某个计数器在洪水期间是否受到影响，并估算通过该计数器的车辆数量变化的幅度和持续时间。这是第一篇能够量化国家网络中所有柜台流量与气候相关变化的论文。结果显示，所有柜台的10％和所有主要道路的23％都有变化。结果使我们能够跟踪中断和绕行路线的配置，恢复时间以及对网络的总体影响。