Locating real-time water level sensors in coastal communities to assess flood risk by optimizing across multiple objectives

Coastal communities worldwide face increasing flood risks due to climate change. Water level sensors offer real-time flood risk information, but optimal sensor placement remains challenging. This study presents a multi-objective optimization approach for strategically locating sensors, incorporating traditional network performance measures (coverage, uncertainty) and flood-specific parameters (hazard estimations, infrastructure exposure, serviceability, social vulnerability). A workflow combining quantitative analysis with local expertise is proposed. The method effectively reduces potential sensor locations, supporting community decision-making and enabling sequential network expansion for hyperlocal flood risk assessment and mitigation.

Iris Tien, Jorge-Mario Lozano, Akhil Chavan