One of the most dangerous challenges to settlements in the UK comes from flooding. Currently, there is extensive map coverage of flood hazards zones in the UK; however, it is increasingly recognised that risk associated with natural hazards cannot be reduced solely by focussing on the hazard. There is also an urgent need for methods of evaluating and mapping flood vulnerability and risk in detail. Despite its significance, conventional flood risk assessment methodologies often underestimate likely levels of vulnerability in areas prone to hazards, yet it is the degree of vulnerability within a community that determines the consequences of any given hazard. The research presented proposes a general methodology to assess and map Coastal Flood Vulnerability and Risk at a detailed, micro-scale level. This captures aspects that are considered crucial and representative of reality (socio-economic, physical and resilient features). The methodology is then applied to a UK case study (city of Portsmouth). Environment Agency flood hazard data, National Census socio-economic data and Ordnance Survey topographic map data have been used to evaluate and map coastal flood vulnerability, examining neighbourhoods within census wards. This led to a subsequent analysis of Coastal Flood Risk, via the combination of a Coastal Flood Vulnerability Index and a Coastal Flood Hazard Index, for the Portsmouth ward Hilsea. This, consequently, identifies potential weaknesses that could lead to more effective targeting of interventions to improve resilience and reduce vulnerability in the long term and provides a basis for hazard and environmental managers/planners to generate comprehensive national/international vulnerability and risk assessments.

In 2017, hurricane Maria caused unprecedented damage and fatalities on the Caribbean island of Dominica. In order to ‘build back better’ and to learn from the processes causing the damage, it is important to quickly document, evaluate and map changes, both in Dominica and in other high-risk countries. This paper presents an innovative and relatively low-cost and rapid workflow for accurately quantifying geomorphological changes in the aftermath of a natural disaster. We used unmanned aerial vehicle (UAV) surveys to collect aerial imagery from 44 hurricane-affected key sites on Dominica. We processed the imagery using structure from motion (SfM) as well as a purpose-built Python script for automated processing, enabling rapid data turnaround. We also compared the data to an earlier UAV survey undertaken shortly before hurricane Maria and established ways to co-register the imagery, in order to provide accurate change detection data sets. Consequently, our approach has had to differ considerably from the previous studies that have assessed the accuracy of UAV-derived data in relatively undisturbed settings. This study therefore provides an original contribution to UAV-based research, outlining a robust aerial methodology that is potentially of great value to post-disaster damage surveys and geomorphological change analysis. Our findings can be used (1) to utilise UAV in post-disaster change assessments; (2) to establish ground control points that enable before-and-after change analysis; and (3) to provide baseline data reference points in areas that might undergo future change. We recommend that countries which are at high risk from natural disasters develop capacity for low-cost UAV surveys, building teams that can create pre-disaster baseline surveys, respond within a few hours of a local disaster event and provide aerial photography of use for the damage assessments carried out by local and incoming disaster response teams.

Dominica, along with several other Caribbean islands, was severely damaged by category-5 Hurricane Maria in September 2017. The hurricane left 68 people dead or missing, marking Maria as the worst natural catastrophe to hit this small island nation. Here, we report the results of our coastal runup field survey in February 2018 and of tide gauge sea-level data analysis. Analysis of tide gauge records shows that the duration of Maria’s surge varied between 2.1 and 2.6 days in the Caribbean region and was 2.1 days at Marigot, Dominica. The surge amplitude was 75 cm in Marigot, which indicates that the size of the surge was small for a category-5 hurricane. The measured field survey runups were from 1.0 to 3.7 m, with the maximum runup at Scotts Head on the southern tip of Dominica. The largest measured runups were concentrated along the west coast of the southern half of the island and consistently decreased northwards. We attribute the observed damage to coastal structures to four mechanisms: surge/wave erosion; surge/wave forces/impacts; debris impacts to coastal structures involving in particular floating tree debris brought to the sea by river floods associated with Hurricane Maria; and intense coastal sedimentation, involving sediment brought to the sea by river floods. A flowchart of the hurricane-driven damage mechanisms is presented which provides the propagating sequence, or cascade, of events that contributed to damage and emphasizes the interactions between different processes in the hurricane.