Large, complex coastal regions often require a combination of interventions to lower the risk of flooding to an acceptable level. In practice, a limited number of strategies are considered and interdependencies between interventions are often simplified. This paper presents the Multiple Lines of Defence Optimization System (MODOS)‐model. This quick, probabilistic model simulates and evaluates the impact of many flood risk reduction strategies while accounting for interdependencies amongst measures. The simulation includes hydraulic calculations, damage calculations, and the effects of measures for various return periods. The application and potential of this model is shown with a conceptual and simplified case study, based on the Houston‐Galveston Bay area. The analyses demonstrate how the MODOS‐model identifies trade‐offs within the system and shows how flood risk, cost, and impact respond to flood management decisions. This improved understanding of the impact of design and planning choices can benefit the discussions in finding the optimal flood risk reduction strategy for coastal regions.

Abstract. Coastal cities combine intensive socioeconomic activities and investments with high exposure to flood hazards. Developing effective strategies to manage flood risk in coastal cities is often a costly and complicated process. In designing strategies, engineers rely on computationally demanding flood simulation models, but they can only compare a limited number of strategies due to computational constraints. This limits the efficacy of standard flood simulation models in the crucial conceptual phase of flood risk management. This paper presents the Flood Risk Reduction Evaluation and Screening (FLORES) model, which provides useful risk information in this early conceptual phase. FLORES rapidly performs numerous simulations and compares the impact of many storms, strategies, and future scenarios. This article presents FLORES and demonstrates its merits in a case study for Beira, Mozambique. Our results demonstrate that expansion of the drainage capacity and strengthening of its coastal protection in the southwest are crucial components of any effective flood risk management strategy for Beira.

Abstract. Coastal cities combine intensive socio-economic activity and investments with high exposure to flood hazards. Developing effective strategies to manage flood risk in coastal cities is often a costly and complicated process. In the design of these strategies, engineers rely on computationally demanding flood simulation models and only compare a few strategies due to computational constraints. This limits the efficacy of standard flood simulation models in the crucial conceptual phase of flood risk management. This paper presents the Flood Risk Reduction Evaluation and Screening (FLORES)-model, which specifically aims to provide useful risk information early on in the planning process. FLORES performs numerous quick simulations and compares the impact of many storms, strategies, and future scenarios. This article presents the screening model and demonstrates its merits in a case study for Beira, Mozambique. Our results demonstrate that expansion of the drainage capacity and strengthening of its coastal protection in the southwest, are crucial components of any effective flood risk management strategy for Beira.

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