Integrating Prediction and Performance Models into Scenario-based Resilient Community Design.

Area of Science:

• Environmental Science
• Urban Planning
• Climate Change Adaptation

Background:

• Urban expansion exacerbates climate change and increases hazard zones, particularly for coastal populations facing sea-level rise and flood risks.
• Land change prediction modeling offers a more adaptable approach to managing urban growth uncertainties and flood risks compared to traditional comprehensive plans.

Purpose of the Study:

• To evaluate the effectiveness of Tampa, FL's current comprehensive plan in adapting urban growth to mitigate flood risk and pollutant load.
• To compare the impacts of three distinct urban growth scenarios on flood risk and environmental factors.

Main Methods:

• Utilized the Land Transformation Model to simulate three urban growth scenarios for Tampa, FL.
• Developed master plans for each scenario and assessed their impacts using the Long-Term Hydrologic Impact Analysis (L-THIA) Low Impact Development Spreadsheet.

Main Results:

• Tampa's current future land use plan shows increased flood exposure, stormwater runoff, and pollutant discharge compared to current conditions.
• Despite appearing better than current development patterns, the existing plan performs worse than a purely resilient growth strategy.

Conclusions:

• The current comprehensive plan for Tampa is less effective in mitigating flood risk and pollutant discharge than a resilient growth approach.
• Scenario-based planning using land change models is crucial for effective adaptation to urbanization and climate change impacts.