In sum, the total weighted daily travel delay costs<sup>18</sup> due to 10-year, 50-year, 100-year, 500-year and 1000year floods are $5,367,000, $8,642,000, $11,628,000, $13,304,000 and $14,374,000 respectively. <mark>When taking flood occurrence probability (i.e. 1in 10, 50, 100, 500 and 1000 years) into consideration, the average daily transport disruption cost weighted by occurrence probability is $1,166,000.</mark> If we assume that on average there are 28 days of flood disruptions on the Kinshasa transportation network then the annualized amount lost to floods is <mark>$32,648,000. It should be underlined that these amounts, because they only consider time lost for commuting purposes and not direct damages or other indirect costs such as disrupted supply chains, constitute a conservative evaluation of the costs of floods in Kinshasa.</mark>

# **5 Conclusion and Discussion**

In Kinshasa, DRC, the combination of pluvial and fluvial floods of multiple return periods impacts all transportation modes and causes a reduction in vehicle speeds, road closures, lengthened daily commute patterns, reduced job accessibility and economic costs due to travel delay. Under wet conditions, the headways for transit modes such as Esprit de Mort increase by 42% from 31 to 44 minutes on average. Flood water accumulation on road surfaces that exceeds 0.2 meters in depth will cause road closures and blockages. Consequently, commuters’ daily trips to and from work need to be rerouted or canceled resulting in pronounced delays in travel time and associated economic costs. Based on our estimation, the total economic cost with respect to daily commuters’ travel delay is $5,367,000 under the 10-year flood scenario. Combined with simulated outputs from multiple flood return periods, the daily weighted average of travel delay cost caused by flood occurrence probability is $1,166,000. It should be noted that this estimation provides a lower bound to the total economic loss due to such type of flooding because it does not account for direct damages to transport infrastructure and for other indirect damages such as <mark>production losses due to supply chain disruptions, or welfare implications of lost accessibility to critical services and supplies.</mark> Several other findings and conclusions emerge from our analysis. First, accessibility to jobs decreases under wet road conditions. On average, the share of jobs that can be reached within one hour will decrease by 0.1% for the walking network, 10.9% for the driving network, and 5.0% for the public transit network. Combined with visualizations of the spatial distribution of loss of job accessibility at TAZ level for three networks (Figure 14), the government as well as planning and design agencies can target specific areas and regions for road fortification and better integration of multiple transport modes to minimize the loss. Second, we observe heterogeneity in travel time impact pattern from floods from both spatial and socio-economical perspectives. In some areas within the Kinshasa city (e.g. Kimbanseke), the income level of its residents is relatively low whereas the travel delay they experience during a 10-year flood event (based on our simulation) is relatively high. The exact opposite pattern can be observed in areas such as Centre Ville, Lingwala, Barumbu, etc. This pattern raises socio-spatial equity issues which are important for public policy considerations. Similar disparities can also be observed for other flood return periods with more extreme values due to travel delays for lower-income groups. These results provide valuable guidelines for planning efforts to target disadvantaged groups and communities for physical and financial aid support. Third, our modified road segment criticality analysis sheds light on the prioritization of road interventions to increase transportation resilience to floods. City officials and transportation planners in Kinshasa aiming to climateproof the city’s transport network face difficult choices in where to start. These results provide some

> 18 The total cost is an estimation of the economic cost to commuters, associated with one day of flooded road conditions in the 10-year flood scenario.

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