Integrated direct and indirect flood risk modeling : development and sensitivity analysis

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<title>Integrated direct and indirect flood risk modeling</title>
<subTitle>: development and sensitivity analysis</subTitle>
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<abstract displayLabel="Summary">In this article, we propose an integrated direct and indirect flood risk model for small- and large-scale flood events, allowing for dynamic modeling of total economic losses from a flood event to a full economic recovery. A novel approach is taken that translates direct losses of both capital and labor into production losses using the Cobb-Douglas production function, aiming at improved consistency in loss accounting. The recovery of the economy is modeled using a hybrid input-output model and applied to the port region of Rotterdam, using six different flood events (1/10 up to 1/10,000). This procedure allows gaining a better insight regarding the consequences of both high- and low-probability floods. The results show that in terms of expected annual damage, direct losses remain more substantial relative to the indirect losses (approximately 50% larger), but for low-probability events the indirect losses outweigh the direct losses. Furthermore, we explored parameter uncertainty using a global sensitivity analysis, and varied critical assumptions in the modeling framework related to, among others, flood duration and labor recovery, using a scenario approach. Our findings have two important implications for disaster modelers and practitioners. First, high-probability events are qualitatively different from low-probability events in terms of the scale of damages and full recovery period. Second, there are substantial differences in parameter influence between high-probability and low-probability flood modeling. These findings suggest that a detailed approach is required when assessing the flood risk for a specific region.</abstract>
<note type="statement of responsibility">E. E. Koks...[et.al]</note>
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<title>Risk analysis : an international journal</title>
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<publisher>McLean, Virginia : Society for Risk Analysis, 1987-2015</publisher>
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<identifier type="issn">0272-4332</identifier>
<identifier type="local">MAP20077000345</identifier>
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<text>04/05/2015 Volumen 35 Número 5 - mayo 2015 </text>
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