Prioritizing Urban Areas For The Deployment Of Hyper-Local Flood Sensors Using Stakeholder Elicitation And Risk Analysis

Abstract

New urban monitoring networks with low-cost sensors can measure hyper-local floods in real-time in hundreds of locations. These novel networks promise enhanced flood risk management, especially within cities where floods can be extremely local. However, current sensor deployment strategies rely on limited metrics (e.g., proximity to densely populated areas) and do not adequately account for the various potential monitoring uses and stakeholders (e.g., emergency responders, critical infrastructure managers, and researchers). Thus, cities have no methodological framework to compare the holistic benefits of deploying new hyper-local sensors in different areas. To address this gap, we develop a framework to prioritize urban areas for sensor deployment based on potential uses for enhanced flood risk management and the exposure of infrastructure and community to high flood hazards at micro-urban scales. This framework includes (1) obtaining stakeholder feedback on the potential uses of sensors and relevant metrics for decision-making on their deployment, (2) quantifying these metrics with publicly available data to integrate them with flood hazard information through probabilistic risk analysis, and (3) combining the metrics to identify areas to be prioritized for sensor deployment. We tested the framework with a case study in New York City, a densely populated urban area with highly heterogeneous communities and infrastructure exposed to high flood hazards. Through elicitation with 45 local stakeholders, we identified 32 potential uses and 58 metrics to prioritize areas for sensor deployment covering flood risk management, the welfare of residents, and the protection of critical infrastructure (e.g., transportation, drainage, and energy). Overall, the proposed framework and case study offer new insights into how modern monitoring networks can help to enhance flood disaster risk management in cities.