A framework to include the (inter)dependencies of Disaster Risk Reduction measures in coastal risk assessment - Cumiskey, Lydia (2019)
Effective coastal risk management often involves the selection and appraisal of Disaster Risk Reduction (DRR) measures. Such measures, however, are rarely implemented in isolation and their (inter)dependencies need to be considered to assess the overall contribution to risk reduction. This paper presents a framework that utilises a pathway-based approach to consider such (inter)dependencies. The framework identifies measures that have the potential to directly influence risk reduction (primary measures) at the individual/household level and how these relate to the implementation of other measures (non-primary). These two types of measures are linked using intermediate pathway factors, which aggregate to the effective uptake and/or operation of primary measure(s) and subsequently represent the direct influence on risk reduction when included in a risk assessment. The approach is demonstrated utilising two coastal risk examples. The case of Varna Bay, Bulgaria highlights a pathway, which explores how developing a coastal Early Warning System (EWS), can enable assets to be moved and saved prior to an event. The Praia de Faro, Portuguese application provides an example of how local risk awareness meetings can support the uptake of property raising to protect against erosion. Past experience, poor trust in authorities, house type/feasibility, transient population and strong community networks are identified as key influencing variables across both cases. The process of considering the (inter)dependencies between measures has potential to lead to improved decision-making and strategy building. The framework developed is flexible in nature and can be applied in many different situations; however, it is one step towards accounting for these (inter)dependencies at the individual/household level. Ex-ante or ex-post survey data, expert judgement and literature have been used to estimate these factors. However, in many cases this good quality data is not available, and is something that national level monitoring strategies, along with the research community, must address.