Between global risk reduction goals, scientific-technical capabilities and local realities: a novel modular approach for multi-risk assessment

Abstract

Abstract. We live in a rapidly changing and globalized society. The increasing connectivity of our economic, social and technical systems, growing urbanization and the consequences of climate change might lead to more complex risks and multi-dimensional vulnerability. The complex relationships between multiple and consecutive natural hazards, exposed population and built environment result in a variety of cascading effects which, if are often not considered appropriately by decision makers, can result to inadequate or even misleading risk management strategies. Thus, hindering efficient prevention and mitigation measures, and ultimately undermining the resilience of societies. International efforts to identify global risks such as within the Sustainable Development Goals, the Sendai Framework for Disaster Risk Reduction 2015–2030 or the Paris Agreement help to raise awareness, set priorities and face such global problems. However, even if the formulated goals for risk reduction are comprehensible in their abstraction, decision-makers still face major challenges when it comes to local implementation. In this paper, we present a conceptual approach for multi-risk assessment which was designed to serve potential users like disaster risk managers, urban planners or operators of critical infrastructures to increase their capabilities. Based on recent scientific and technical capabilities, we developed a tool through an iterative participative approach which has allowed users to explore various scenarios of multiple hazards, cascading effects and their impacts. As an illustrative example, the experiences during this stimulating process are documented for Lima Metropolitan area (Peru), a megacity exposed to various natural hazards, among them, earthquakes and tsunamis. We believe that such an approach for exploring, describing and quantifying different What-if scenarios can constitute a valuable approach for understanding complex multi-risk processes, preparing for such situations, and serving as a good practice that can be replicated for other areas of interest in the future.