Abstract

The St. Johns River, located in northeast Florida, USA, is a large watershed characterized by relatively flat topography, porous soils, and increasing urbanization. The city of Jacksonville, Florida is located near the downstream terminus of the river near the Atlantic Ocean. The lower portion of the watershed located downstream of Lake George is subjected to tidal exchange and storm surge from tropical storms and hurricanes as well as extra-tropical winter storms. Extreme flood events in the Lower St. Johns River can be caused by rain-driven runoff, high tide, storm surge or any combination of the three. This study examines the range of potential extreme flood discharges caused by rain-driven runoff within six larger sub-basins located in the Lower St. Johns River with special emphasis on the Pablo Creek sub-basin. The study uses multiple methods including published flood insurance data, two statistical hydrology methods, and model simulations to estimate an array of flood discharges at varying return frequencies. The study also examines the potential effects on flood discharges from future land use changes and the temporal distribution of rainfall. The rain-driven flood discharge estimates are then fit to a normal distribution to convey the overall risk and uncertainty associated with the flood estimates. Overall, the study revealed that a wide range of reasonable rainfall-driven flood estimates are possible using the same data sets. The wide range of estimates will help inform future resiliency projects planned in the study area by providing a more realistic set of bounds with which planning can proceed. The estimates derived herein for the Pablo Creek sub-basin can be combined with the independent or dependent effects of tide and storm surge in order to characterize the total flood resiliency risk of the region.

Highlights

  • Extreme flood estimation is a continuously evolving field of research

  • The HSPF model area is approximately 82% of the drainge area reported in the Federal Emergency Management Agency (FEMA) Flood Insurance Study (FIS)

  • The HSPF model estimates and the statistical estimates were overall low compared to the FEMA FIS estimates in Pablo Creek

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Summary

Introduction

Extreme flood estimation is a continuously evolving field of research. The 10-, 25-, 50-, and 100-year return frequency floods (e.g. the 10%, 4%, 2%, and 1% annual exceedance probability floods) have been assessed using multiple methodologies including: the use of the St. Johns River Water Management District’s (SJRWMD) HSPF hydrologic model, statistical computations using of the Log-Pearson Type III and Power Law distribution, and analysis of existing Federal Emergency Management Agency (FEMA) Flood Insurance Study (FIS) estimates. Johns River Water Management District’s (SJRWMD) HSPF hydrologic model, statistical computations using of the Log-Pearson Type III and Power Law distribution, and analysis of existing Federal Emergency Management Agency (FEMA) Flood Insurance Study (FIS) estimates Sensitivity of parameters such as land-use change, precipitation frequency values (median versus 90th percentile), and rainfall temporal distribution

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