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A Bayesian probabilistic approach for impacts of sea level rise on coastal engineering design practice

机译：贝叶斯概率方法研究海平面上升对沿海工程设计实践的影响

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摘要

The real impact of sea level rise (SLR) on coastal and ocean engineering infrastructures is anticipated to be significant. The associated huge costs of coastal flooding and lasting socio-economic crisis would require planners, decision-makers and engineers to use effectively all available knowledge and data to optimize flood defense protection systems. In this paper, we introduce a Bayesian approach that integrates knowledge from previous performance history of structures (data, models and analysis) with more recent information from the simulations performed using the latest data, methods and modeling technology. These two sets of knowledge and information on past and present status of system contain various uncertainties and errors introduced by different input sources and analysis methods. We employ the concept of global uncertainty to quantify the total uncertainty affecting the design, functionality and maintenance of coastal flood defense systems in order to reduce damages resulting from the SLR and other extreme water level changes (e.g., storm surges by hurricanes, increased precipitation and ice melting). Our objective in this paper is to show coastal engineers how to use the prior knowledge with the most current information to improve the safety of flood defense systems. We demonstrate the proposed method in an example for the failure analysis of the 17th Street Rood Wall in New Orleans, where we estimate uncertainties that affected the design of the Ⅰ-wall. We provide a methodology that integrates the contribution of SLR with all other available prior information to determine uncertainty levels for failure analysis of the flood defenses. Various uncertainties are present in engineering practice, explicit or implicit, and quantification of these is essential to safety and efficacy of coastal flood protection systems.
机译：预计海平面上升（SLR）对沿海和海洋工程基础设施的实际影响是巨大的。沿海洪水和持续的社会经济危机带来的巨额成本将需要规划者，决策者和工程师有效利用所有可用的知识和数据来优化防洪保护系统。在本文中，我们介绍了一种贝叶斯方法，该方法将以前结构（数据，模型和分析）的性能历史中的知识与使用最新数据，方法和建模技术进行的模拟中的最新信息相结合。这两套关于系统过去和当前状态的知识和信息包含由不同输入源和分析方法引入的各种不确定性和错误。我们采用全球不确定性的概念来量化影响沿海防洪系统设计，功能和维护的总不确定性，以减少SLR和其他极端水位变化（例如飓风带来的风暴潮，降水增加和融冰）。本文的目的是向沿海工程师展示如何利用现有知识和最新信息来提高防洪系统的安全性。我们以新奥尔良第17街屋顶墙的破坏分析为例，演示了所提出的方法，其中我们估计了影响Ⅰ墙设计的不确定性。我们提供了一种方法，该方法将SLR的贡献与所有其他现有的先验信息相结合，以确定洪水防御失效分析的不确定性级别。工程实践中存在各种不确定性，无论是明示性还是隐性性，量化这些不确定性对于沿海防洪系统的安全性和有效性至关重要。

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