The key aspect for the quantification of indirect impacts of flooding is the assessment of the disruption of the transportation service considering social and economic consequences. To investigate how flooding can affect road transportation, it is essential to analyze interaction during the flood event itself, as well as on the following days. In this work, two static and dynamic traffic models are applied to a study zone for quantification of the performance and functionality of the network during the flood and after the failure of infrastructure components. A mesoscopic simulation was applied to identify the traffic disruption in the face of flood events. This simulation is capable of considering the road network model, assigning trip paths with the impact of road closures and speed reductions, and evaluating travel time and vehicle volume redistribution in a given disruption scenario. By comparing the traffic analysis results (travel time, travelled distance and street speed changes) in normal and flooded situations, the impact of flooding on a transportation network could be examined. Moreover, modelling outputs from a case study in the Santarém region (Portugal) indicated that in analyzing the flood impacts on a traffic network, even non-flooded infrastructures must be taken into account because of their service disruption.

There is a relationship between choosing an activity and duration of that activity, especially for non-mandatory ones. Some previous studies have analyzed the decisions about an activity type and duration independently, though some others have used joint models. This paper contributes to the body of knowledge through using Nested-logit and Copula-based models for assessing the existence of interdependency or a hierarchy between non-mandatory activity choice and the relative duration. In the Nested-logit model, it is assumed that error terms of these decisions are interrelated, though one is influenced by another. In contrast, the Copula-based model can accommodate spatial error correlation across observational units without imposing a restrictive distribution assumption on the dependency structures between the error components. The data from Qazvin, a city in Iran, are used for estimating both Nested-logit and Copula-based models and the best variables explaining both choices for each model have been selected. The final models were compared in terms of log-likelihood at convergence and adjusted likelihood ratio index. The results indicated that there are some common influential observed and unobserved factors between these decisions. Also, Copula-based joint model with ρ 0 2 equals to 0.134 outperforms Nested-logit models and provides a better explanatory power.

The indirect impacts of flooding on transportation networks include, among others, consequences of the service disruption for the users. Indirect impacts are of a wider scale and with a longer incidence in time than direct impacts. The key aspect for the quantification of indirect impacts of flooding is the assessment of the disruption of the transportation service, with social and economic consequences. In this work, a traffic model for a pilot zone is constructed for accurate quantification of the functionality of the network after the failure of infrastructure components such as road segments and bridges. A mesoscopic simulation, which is capable of building a road network model, assigning trip paths with the impact of road closures, and evaluating travel time and vehicle volume redistribution in a given disruption scenario, was used to identify the traffic disruption in the face of flood events. Modelling outputs from a case study in the Santarém region of Portugal indicate which roads are more congested in a day. A comparison between the baseline and a flood scenario yields the impacts of that flood on traffic, estimated in terms of additional travel times and travel distances. Therefore, simulating and mapping the congestion can largely facilitate the identification of vulnerable links.

As there is a staggering increase in flooding worldwide, many countries have prioritized sustainability of their transportation sector through flood impact prediction to support the transition during flooding. As such, research regarding the flood impacts on transportation has dramatically increased in recent years. Hybrid methods play an important role in simulating the flood situation and its impacts on traffic networks. This article offers a systematic literature review of existing research which employ hybrid methods to assess the indirect impacts of flooding on transportation. In this study, 45 articles are reviewed systematically to answer 8 research questions regarding modeling the indirect impacts of flooding on transportation. The hybrid techniques observed in the existing literature are discussed and along with the main barriers to precise prediction of flooding’s indirect impacts on transportation, future research directions are also suggested.