Integrated Direct and Indirect Flood Risk Modeling: Development and Sensitivity Analysis

被引:125
|
作者
Koks, E. E. [1 ]
Bockarjova, M. [2 ]
de Moel, H. [1 ]
Aerts, J. C. J. H. [1 ]
机构
[1] Vrije Univ Amsterdam, Inst Environm Studies IVM, NL-1081 HV Amsterdam, Netherlands
[2] Vrije Univ Amsterdam, Dept Spatial Econ, NL-1081 HV Amsterdam, Netherlands
关键词
Flood duration; flood risk modeling; indirect losses; input-output model; CLIMATE-CHANGE; DAMAGE; UNCERTAINTY; DISASTER; INOPERABILITY; CONSEQUENCES; ADAPTATION; RESILIENCE; IMPACT;
D O I
10.1111/risa.12300
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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.
引用
收藏
页码:882 / 900
页数:19
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