Advancing Scenario Planning to Prepare for Uncertain Climate Change: Future Urban Growth Prediction and Flood Vulnerability

The people and assets endangered by flood risks due to sea level rise and coastal population increase are increasing. Complex and unpredictable future circumstances necessitates a better scenario-based planning; helping to make better decisions through examining plausible future probabilities. Though it has value in urban planning, scenario planning has been limited to a single preferred plan and impact evaluation. To advance scenario planning for uncertain future urban growth and climate change, this research exemplifies scenario making and impact evaluation using the city of Tampa as a case site. It answers “How prepared are U.S. coastal cities for future urban growth and flood risks?” In scenario making, this research creates flood risk and future urban growth scenarios in lieu of sea level rise using the Land Transformation Model, a GIS-based Artificial Neural Network land use prediction model. For impact analyses, first, three different urban growth scenarios are evaluated by comparing urban flood exposure at a city and neighborhood level. Second, plan policies are examined with predicted urban growth and flood risks in eight highly clustered future urban neighborhoods. The findings show that the growth as land use plan scenario places less urban areas exposed to flood risks than the growth as business as usual, but much larger urban flood exposure than the resilient growth scenario at the city level. Even at the neighborhood level, more amounts of neighborhoods in the planned growth scenario are vulnerable to flood risks than in the business as usual scenario In plan preparation, the findings show that Tampa’s policies do not do enough to prepare for future climate change since the policies are based on the current climate pattern, and some policies are assigned in wrong locations. The scenario matrix (urban growth and flood risk scenarios) enables the ability to examine planning problems at multiple scales. The results of the impact analyses confirm dilemmas in urban planning: a regional solution can be worse in a neighborhood, and a good policy in the wrong place can work negatively