Flood risk assessment and associated uncertainty
Flood risk assessment and associated uncertainty
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DOI：
10.5194/nhess-4-295-2004
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发表时间：
2004-01-01
影响因子：
4.6
通讯作者：
Blöschl, G
中科院分区：
文献类型：
--
作者：
Apel, H;Thieken, AH;Blöschl, G
洪灾减灾战略应建立在对洪灾风险进行全面评估的基础上，并彻底调查与风险评估程序有关的不确定性。在“德国自然灾害研究网络”(DFNK)内，“洪水风险分析”工作组调查了洪水过程链，从降水、流域径流的产生和集中、洪水路线、河网中的洪水、可能的防洪措施失效、洪水淹没到经济损失。工作组用不同尺度的确定性空间分布模型代表了这些进程中的每一个。虽然这些模型提供了对洪水过程链的必要了解，但由于它们的复杂性和对CPU时间的高要求，它们不适合进行风险和不确定性分析。因此，我们开发了一个随机洪水风险模型，该模型由与过程链组件相关联的简化模型组件组成。我们根据复杂确定性模型的结果对这些模型组件进行了参数化，并将它们用于蒙特卡罗框架中的风险和不确定性分析。蒙特卡罗框架分成两个层次，分别代表两种不同的不确定性来源：射电不确定性(由于自然和人为的可变性)和认知性不确定性(由于对系统的不完全了解)。该模型允许我们在蒙特卡罗框架的第一层中计算不同强度事件的发生概率以及焦油地区的预期经济损失，即评估经济风险，并在第二层中得出与这些风险相关的不确定性界限。还有可能确定个别不确定性来源对总体不确定性的贡献。结果表明，由认知源引起的不确定性显著改变了仅用主观不确定性得到的结果。该模型被应用于科隆下游莱茵河的河段。
Flood disaster mitigation strategies should be based on a comprehensive assessment of the flood risk combined with a thorough investigation of the uncertainties associated with the risk assessment procedure. Within the "German Research Network of Natural Disasters" (DFNK) the working, group "Flood Risk Analysis" investigated the flood process chain from precipitation, runoff generation and concentration in the catchment, flood routing, in the river network, possible failure of flood protection measures, inundation to economic damage. The working group represented each of these processes by deterministic, spatially distributed models at different scales. While these models provide the necessary understanding of the flood process chain, they are not suitable for risk and uncertainty analyses due to their complex nature and high CPU-time demand. We have therefore developed a stochastic flood risk model consisting of simplified model components associated with the components of the process chain. We parameterised these model components based on the results of the complex deterministic models and used them for the risk and uncertainty analysis in a Monte Carlo framework. The Monte Carlo framework is hierarchically structured in two layers representing two different sources of uncertainty, aleatory uncertainty (due to natural and anthropogenic variability) and epistemic uncertainty (due to incomplete knowledge of the system). The model allows us to calculate probabilities of occurrence for events of different magnitudes along with the expected economic damage in a tar-et area in the first layer of the Monte Carlo framework, i.e. to assess the economic risks, and to derive uncertainty bounds associated with these risks in the second layer. It is also possible to identify the contributions of individual sources of uncertainty to the overall uncertainty. It could be shown that the uncertainty caused by epistemic sources significantly alters the results obtained with aleatory uncertainty alone. The model was applied to reaches of the river Rhine downstream of Cologne.