Flood footprint of the 2007 floods in the UK: The case of the Yorkshire and The Humber region

Abstract

International headlines over the last few years have been dominated by extreme weather events, and floods have been amongst the most frequent and devastating. These disasters represent high costs and functional disruptions to societies and economies. The consequent breakdown of the economic equilibrium exacerbates the losses of the initial physical damages and generates indirect costs that largely amplify the burden of the total damage. Neglecting indirect damages results in misleading results regarding the real dimensions of the costs and prevents accurate decision-making in flood risk management. To obtain an accurate assessment of total flooding costs, this paper introduces the flood footprint concept, as a novel accounting framework that measures the total economic impact that is directly and indirectly caused to the productive system, triggered by the flooding damages to the productive factors, infrastructure and residential capital. The assessment framework account for the damages in the flooded region as well as in wider economic systems and social networks. The flood footprint builds on previous research on disaster impact analysis based on Input-Output methodology, which considers inter-industry flows of goods and services for economic output. The framework was applied to the 2007 summer floods in the UK to determine the total economic impact in the region of Yorkshire and The Humber. The results suggest that the total economic burden of the floods was approximately 4% of the region's GVA (£2.7 billion), from which over half comes from knock-on effects during the 14 months that the economy of Yorkshire and The Humber last to recover. This paper is the first to apply the conceptual framework of flood footprint to a real past event, by which it highlights the economic interdependence among industrial sectors. Through such interrelationships, the economic impacts of a flooding event spill over into the entire economic system, and some of the most affected sectors can be those that are not directly damaged. Neglecting the impact of indirect damages would underestimate the total social costs of flooding events, and mislead the correspondent actions for risk management and adaptation

Methodology and application of flood footprint accounting in a hypothetical multiple two-flood event

“…As the most common of natural disasters, floods are selected as the main type of multiple natural disaster in this study and the concept of flood footprint that is proposed by Mendoza-Tinoco et al [25] is applied here to indicate the total economic impact caused by floods through direct and indirect methods. In particular, direct flood footprint (DFF) analysis shows the direct damage to physical capital, people and natural resources; while the indirect approach refers to the physical damage-induced influence on an economic system during the post-disaster recovery period.…”

Analysis of the Economic Ripple Effect of the United States on the World due to Future Climate Change

“…In this paper, the standard parameters are defined based on the existing literature and data from the WorldBank (): The economic parameters are set in combination with the parameter set of Hurricane Katrina in the United States from Hallegatte () and the international trade time to import and export from the WorldBank (). The threshold of the parameter uncertainty range is set to upward and downward variations of 30% of the standard parameters; this range refers to the flood footprint model (Mendoza‐Tinoco et al, ), which is influenced by capital and labor.…”

“…In addition, to verify the robustness of the model, we defined different verification groups to determine whether the model simulation results are orderly and stably distributed within the scope of uncertainty (Mendoza‐Tinoco et al, ). In addition, the parameter values of each group are taken in accordance with the uncertainty range in the interval of 5%, that is, a total of 13 groups.…”

“…The uncertainty of the model parameters is mainly due to the lack of elaborate and efficient data with which to calibrate the parameters. In this paper, the standard parameters are defined based on the existing literature and data from the WorldBank (2012) In addition, to verify the robustness of the model, we defined different verification groups to determine whether the model simulation results are orderly and stably distributed within the scope of uncertainty (Mendoza-Tinoco et al, 2017). In addition, the parameter values of each group are taken in accordance with the uncertainty range in the interval of 5%, that is, a total of 13 groups.…”

Were the floods in the UK 2007 and Germany 2013 game-changers?

“…These findings are supported by other research. In the UK, at the end of May, 11-12 months after the floods, local authorities estimated that about 75% of households were back in their homes [25] and the economy of the Yorkshire and Humberside Region had returned to pre-disaster production levels within 14 months [55]. In Germany, a survey of 752 flood-prone residents 18 months after the event revealed that 52% of respondents had almost fully repaired the damage to their buildings and 28% of respondents said they were back to normal [33].…”