Disruptions to transportation networks by natural hazard events cause direct losses (e.g. by physical damage) and indirect socio-economic losses via travel delays and decreased transportation efficiency. The severity and spatial distribution of these losses varies according to user travel demands and which links, nodes or infrastructure assets are physically disrupted. Increasing transport network resilience, for example by targeted mitigation strategies, requires the identification of the critical network segments which if disrupted would incur undesirable or unacceptable socio-economic impacts. Here, these impacts are assessed on a national road transportation network by coupling hazard data with a transport network model. This process is illustrated using a case study of landslide hazards on the road network of Scotland. A set of possible landslide-prone road segments is generated using landslide susceptibility data. The results indicate that at least 152 road segments are susceptible to landslides, which could cause indirect economic losses exceeding £35 k for each day of closure. In addition, previous estimates for historic landslide events might be significant underestimates. For example, the estimated losses for the 2007 A83 'Rest and Be Thankful' landslide are £80 k day À1 , totalling £1.2 million over a 15 day closure, and are ∼60% greater than previous estimates. The spatial distribution of impact to road users is communicated in terms of 'extended hazard impact footprints' . These footprints reveal previously unknown exposed communities and unanticipated spatial patterns of severe disruption. Beyond cost-benefit analyses for landslide mitigation efforts, the approach implemented is applicable to other natural hazards (e.g. flooding), combinations of hazards, or even other network disruption events. perturbation to network operation (i.e. reduced access, travel delay and costlier routes). Consequently landslide hazard impact and population exposure is distributed far beyond the hazard's physical location. Critical network segments are those characterised by a high consequence of failure generally irrespective of likelihood [4,5]. A poignant example is the estimated £3.0 billion regional economic loss incurred in the South West, UK [6] by damage to 40 m of railway line during storm water levels exceeding previous maxima in 100 year historical records [7]. The identification of critical network segments is integrated within network management guidelines [8,9]. However, these operational assessments are limited to road segment