Vulnerability, understood as the conditions determined by physical, social, economic and environmental factors or processes that increase the potential for an individual, a community, assets or systems to be negatively affected by hazards, is a key component when assessing tsunami risk. Vulnerability can be affected by human interventions. Hence, the study of vulnerability is essential to support decision-making (e.g., land use planning and emergency planning) for more effective risk management. Vulnerability is most commonly represented through a vulnerability function that expresses the likelihood of achieving a value of a loss parameter for increasing values of a hazard intensity measure.

In a time of climate emergency due to global warming, nature-based coastal defence systems are attractive solutions for flood mitigation and adaptation. Coastal forests such as mangroves have received a growing interest for their disaster mitigation effectiveness such as water flow energy dissipation, hence helping communities to become more resilient (Iimura & Tanaka, 2012). The role of coastal forests as a defence measure was highlighted in the aftermath of the 2004 Indian Ocean Tsunami, which claimed the lives of more than 200,000 people and displaced millions more across fourteen countries. Post-disaster damage observations indicated that forests, particularly mangroves, reduced the impact of the tsunami wave in some locations. As a result, significant international relief and reconstruction efforts focused on extensive forest replantation of coastlines (Satake, 2014).

The role of coastal vegetation in reducing the severity of tsunami waves has been studied since. Several studies using physical modelling and computational approaches have provided insights into the wave attenuation provided by coastal vegetation, in terms of relationships between incident hydrodynamic conditions, forest configurations and wave height decay. However, there are still many gaps in knowledge, particularly in quantifying the efficacy of coastal forests in reducing inland hydrodynamic conditions (Tomiczek et al., 2020). It is therefore essential to improve the understanding on how wave heights, velocities and runup are influenced by the characteristics of the “obstacles”, e.g. the forest density, as well as the incident hydrodynamic conditions, e.g. the wave period. This study aims to address these questions conducting physical experiments using the novel pneumatic Tsunami Simulator (TS) developed by HR Wallingford together with UCL (Rossetto et al., 2011).