Protecting Energy Infrastructure against the Uncertainty of Future Climate Change: A Real Options Approach

Abstract

The coastal impacts of climate change, including flooding and erosion due to storms and sea-level rise, and the possible adaptation responses have been studied using very different approaches; from very detailed site-specific, process-based investigations and interventions to global macroeconomic assessments of coastal zone vulnerability. This paper presents a flood defense real option analysis methodology that values potential investment decisions made in the building and maintaining of flood defenses around electricity infrastructure at local spatial scales for a large region. Real option analysis embraces uncertainty in future climate conditions and flexibility in the management of investment projects to produce a more precise optimal outcome than attained with traditional discount cash flow analysis alone. The method uses high-level analysis from flood inundation models to assess the cost of flooding for energy infrastructure at the present-day up to the highest plausible sea-level rise for the UK in 2100 known as the H++ scenario, which projects a sea-level rise of 1.8 m. These costs feed into a real option valuation model able to identify which energy infrastructure will benefit from investment, and when. This northwest UK study identifies two infrastructure sites that, today, would benefit from flood defence investment over discount cash flow analysis, increasing to an additional 14 in 2050. Using this method has identified 46 sites that would benefit from deferring flood defence investment now, reducing to 35 sites in 2050. This method of project valuation can be applied to any feature within the floodplain, e.g. infrastructure or residential housing, making it an adaptable and useful tool in identifying vulnerable features that require investment to ensure they stay resilient to extreme flood events in the future. This work is the result of an inter-disciplinary collaboration between hydrodynamic modelling, flood risk assessment and economics. The outputs of which are ideal to be fed into a decision-support tool, allowing stakeholders to interrogate and disseminate information about the spatial locations they are interested in.