Advancing Flood Risk Prediction in Coastal Urban Areas through Geospatial Modeling: A case study of Greater Boston Metropolitan Area.

Keywords: Flood Risk Prediction, Geospatial Modeling, Multi-Criteria Evaluation, Climate Change Adaptation, Vulnerability
Abstract Type: Paper Abstract

Abstract

The increasing occurrence of flooding in coastal urban areas calls for innovative approaches to flood risk prediction and assessment. This study focuses on improving the prediction of flood risks through an advanced geospatial model in the Greater Boston Metropolitan area, an urban area that is susceptible to the growing effects of storms. The main objective of this paper is to identify flood-prone areas within the Greater Boston Metropolitan area that are currently unaccounted for in FEMA flood maps, particularly considering changing precipitation patterns. The study adopts eight variables including elevation, slope, precipitation, land use, storm surge, distance to streams, infiltration rate, and soil types of the study area to model flood risk. The study employs a Multi-Criteria Evaluation to develop a multi-tiered flood risk classification system, in which the risks are classified on the basis of the weights of the variables. The model is then used to assess the vulnerability of critical infrastructure and communities in high flood risk areas. It employs spatial statistical techniques to quantify the potential economic losses, infrastructure damage, and displacement resulting from flooding in these areas. The results are expected to have an influence on the formulation of urban planning and disaster management measures that are able to place a more robust shield around communities within the flood zone. By providing detailed flood risk insights, this research directly supports climate adaptation efforts by equipping urban planners, policymakers, and local leaders with actionable data to mitigate potential flood impacts driven by climate change.