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

Abstract Coastal communities around the world are experiencing increased flooding. Water level sensors provide real-time information on water levels and detections of flood risk. Previous sensor installations, however, have relied qualitative judgments or limited quantitative factors to decide locations. Here, we a method optimally place across community. We utilize multi-objective optimization approach, including traditional measures network performance such as coverage uncertainty, new flood-specific parameters hazard estimations (flood likelihood, critical infrastructure exposure), serviceability (sensor accessibility), social vulnerability (socio-economic index, vulnerable residential index). propose workflow combining analyses with local expertise experience. show is able reduce set possible locations just 1.3% full solution set, supporting effective feasible community decision-making. The also supports sequential expansion network, creating that provides detailed accurate at hyperlocal for risk assessment mitigation in coastal communities.