Mean and extreme sea-level uncertainties, as well as uncertainty about future flood exposure, hinder the risk-based optimisation of flood protection investments. To deal with these uncertainties, cost-benefit analysis (CBA) and methods for robust decision-making can be combined. This paper sequentially applies CBA, robust optimisation methods and info-gap analysis to find efficient and robust coastal flood protection strategies for the German Baltic Sea coast. The CBA results suggest that – under flood risk assumptions – a share of the coast of Schleswig-Holstein (9.3–10.1%; 60–65 km) and Mecklenburg-Vorpommern (4.1–10.0%; 78–189 km) with relatively high flood exposure, might currently be under-protected from a social welfare perspective. Present Value estimates of regional investment costs of five regret or loss minimising strategies range from 1.7 to 4.8 billion Euro across robustness metrics at 3% discounting. The info-gap analysis suggests that some of these strategies will fail to prevent large-scale damages under high-end scenarios. We conclude that a multi-method cost-benefit approach can be used to narrow down the number of solutions that are both potentially efficient and sufficiently robust by investigating strategy performance within, across and beyond predefined scenarios.

平均和极端的海平面不确定性以及未来洪水风险的不确定性阻碍了基于风险的防洪投资优化。为了应对这些不确定性，可以结合成本效益分析（CBA）和可靠的决策方法。本文依次运用CBA，鲁棒性优化方法和信息缺口分析来为德国波罗的海沿岸找到有效而鲁棒的沿海防洪策略。CBA结果表明，在洪水风险假设下，洪水相对较高的石勒苏益格-荷尔斯泰因海岸（9.3-10.1％； 60-65公里）和梅克伦堡-前波美拉尼亚州（4.1-10.0％； 78-189公里）的份额从社会福利的角度来看，目前可能没有受到足够的保护。五种最小化后悔或损失策略的区域投资成本的现值估计范围为1。7个到48亿欧元的耐用性指标（折现3％）。信息差距分析表明，其中一些策略将无法防止高端情况下的大规模破坏。我们得出结论，通过研究预定义方案内，跨方案外以及方案外的策略性能，可以使用多方法成本效益方法来缩小可能有效且足够健壮的解决方案的数量。