Coastal community water infrastructure is increasingly vulnerable to flooding from a range of causal events operating at different spatial and temporal scales. Along with sea level rise, king tides, storm surges, extreme rainfall runoff, ground water inundation and salt water intrusion challenge emergency management, urban planning, and public health in coastal communities. Using case studies in Charleston (SC) and Morehead City (NC), this project developed geospatial methods for risk assessment of urban water and wastewater infrastructure. The geospatial analysis focused on vulnerability by integrating geospatial hazard models, water infrastructure, and attendant human impacts to provide guidance for emergency managers, urban planners, public utilities, and health care providers. Risk maps detailed spatial patterns of nuisance flooding and king tides, storm surges, and extreme precipitation-related inundation impacting centralized or on-site wastewater systems, potable water supply, direct human exposure to floodwaters, and provision of emergency health services. Results highlight the differential patterns of vulnerability and implications for public health and emergency planning. Methodological results identified variable data quality and model uncertainity. Implications for improving integrative public health risk assessments, emergency management, and planning are drawn for developing new multi-hazard resiliency planning information. Portability of the approach is also reviewed with consideration of challenges in Hampton Roads, Virginia.

Dr. Tom Allen is a geographer and faculty member in the Department of Political Science & Geography at Old Dominion University (ODU). A native of Hampton Roads, Tom earned his B.S. in Geography at ODU and Ph.D. in Geography at the University of North Carolina at Chapel Hill. Current research interests focus on human-environment interactions in coastal and marine environments, climate change and human and ecosystem health, coastal remote sensing, spatial analysis, and interdisciplinary applications of Geographic Information Science.

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