## 2 Literature Review  
Several descriptive research works have been done to evaluate the impacts of floods on a road network. The Department for Transport UK [9] assessed one day of flooding. Their results showed that this flood event on the UK's road network caused about 2% of the annual delays all around the country. [PERSON] and [PERSON] [10] reported how a 15-min ride turned into a two-hour journey after many bridges in Workington collapsed. As another example, the Desmond storm cost EUR3.8 million in traffic disruption in Ireland, according to [PERSON] et al. [11]. Based on these research examples, flooding impacts significantly affect transportation networks and their users. The key aspect for the quantification of indirect impacts of flooding depends on reliably assessing the magnitude of the disruption of the transportation service. To this end, traffic models have been used to understand the behavior of road networks under disruption scenarios, i.e., to simulate how traffic flows through an impaired network with closed or reduced speed links while satisfying both demand and capacity [12]. For example, [PERSON] et al. [13; 14] analyzed the effects of flood depths and flow speeds on vehicle stability. Other researchers have worked on the relationship between standing-water depths on road surfaces and vehicular speed [15; 16]. They investigated the significance of the flooded roads within a network. Most approaches found in the literature have used macroscopic traffic models for this purpose [6]. For example, [PERSON] et al. [17] found that climate change might possibly double both travel distance and time, while [PERSON] et al. [18] found that traffic delays were a greater concern than the increased distance. It is reasonable to assume that because the urban environment provides numerous rerouting alternatives, the travel distance may not increase as much as the travel time due to traffic congestion. The robustness and vulnerability of the traffic network in York, UK, were studied by [PERSON] and [PERSON] [19]. Nine streets were identified as being at risk of floods and were either closed to traffic or had their capacity decreased. The vulnerability and resilience indices were derived based on the assumption that each flooded street is independent. This may be considered unrealistic because flooding normally impacts a greater area than just one street. Despite this simplification of the problem, they could identify the most vulnerable streets. All of this research used macroscopic traffic modelling, which is capable of representing congestion or diversion in a large region but cannot represent individual vehicles or people on the network. Thus, the dynamics of the transportation system during a flooding event cannot be properly addressed. Conversely, other modelling approaches such as microscopic simulation provide very precise results since individual vehicles are tracked on the network at small time steps [20]. [PERSON] et al. [21] performed a micro-scale modelling of traffic for the Italian city of Messina considering network disruptions for thousands of possible earthquake scenarios in order to sample uncertainties within a probabilistic framework. However, microsimulation is rarely used to represent large geographical areas because of the higher computational cost and the level of detail needed regarding the input data. Thereby, a mesoscopic simulation, which falls between these two modelling approaches, can portray a feasible alternative for the assessment of flood impacts in transportation networks [22]. Mesoscopic modelling can represent large geographic areas with more precise results than macroscopic simulation since vehicles in the transport system are represented, while the computational cost is reasonably lower in comparison to microscopic simulation [23]. In a mesoscopic model, every individual vehicle is considered with a specific origin, destination, departure time, and routes, while their movements are defined following a set of macroscopic traffic flow relations [24].