This seminar will introduce three map-based decision support tools for future adaptation planning:
Sea level rise and flood mappers typically show static GIS-based “bathtub” extrapolations of how floods or daily high tides would rise and spread further out into floodplains. Dynamic model-based flood mappers have a greater capacity for merging flood water sources, simulating the changes in flooding including possible interactions between sea level rise, tides, storm surge and river flows. The Hudson River Flood Impact Decision Support System is an interactive map application that allows users to evaluate the scale of potential flooding for tidally-affected shorelines of the Hudson River Valley and Westchester County under a variety of sea level rise and storm scenarios. HRFIDSS was created by CIESIN and Stevens Institute of Technology with funding provided by the New York State Energy Research and Development Authority (NYSERDA).
Sea level rise and flood mappers also rarely demonstrate how flood adaptation can reduce the flood areas and depths. We will also describe the general concept of flood adaptation mappers, show an example of such a mapper, and outline possibilities for potential future development. AdaptMap is another dynamic model-based flood mapping web‐tool, and demonstrates the effects of nature-based features on flood hazard zones for the highly populated areas surrounding Jamaica Bay, New York City.
Visionmaker is a tool designed to encourage community participation in adaptation planning in New York City. Users from landscape architects to schoolchildren, can define their own area of interest, query the pre-Contact and contemporary ecosystems, and then make their own “vision” of the future by changing ecosystems, lifestyles, and climate scenarios. Integrated models estimate benefits in terms of the carbon cycle, water cycle, and biodiversity of the user’s choices. Climate parameterizations and future flooding are based on the New York City Panel on Climate Change projections. The tool is meant for individual or community-based rapid iteration, conceptualization, and sharing to encourage ecological democracy.