Floodplain Risk Analysis Using Flood Probability and Annual Exceedance Probability Maps

This research presents two approaches to determining the effects of natural variability and model uncertainty on the extents of computed floodplain boundaries. The first approach represents the floodplain boundary as a spatial map of flood probabilities -- with values between 0 and 100%. Instead of representing the floodplain boundary at a certain recurrence interval as a single line, this approach creates a spatial map that shows the probability of flooding at each point in the floodplain. This flood probability map is a useful tool for visualizing the uncertainty of a floodplain boundary. However, engineers are still required to determine a single line showing the boundary of a floodplain for flood insurance and other floodplain studies. The second approach to determining the effects of uncertainty on a floodplain boundary computes the annual exceedance probability (AEP) at each point on the floodplain. This spatial map of AEP values represents the flood inundation probability for any point on the floodplain in any given year. One can determine the floodplain boundary at any recurrence interval from this AEP map. These floodplain boundaries include natural variability and model uncertainty inherent in the modeling process. The boundary at any recurrence interval from the AEP map gives a single, definite boundary that considers uncertainty. This research performed case studies using data from Leith Creek in North Carolina and the Virgin River in southern Utah. These case studies compared a flood probability map for a certain recurrence interval with an AEP map and demonstrated the consistency of the results from these two methods. Engineers and planners can use floodplain probability maps for viewing the uncertainty of a floodplain boundary at a certain recurrence interval. They can also use AEP maps for determining a single boundary for a certain recurrence interval that considers all the natural variability and model uncertainty inherent in the modeling process.

Name thesis:degree_name

PhD

Grantor dc:publisher

Brigham Young University - Provo

Author dc:creator

• Smemoe, Christopher M.

• Floodplain delineation
• Hydrology
• Hydraulics
• Hydrologic and Hydraulic Modeling
• Uncertainty
• Risk Analysis
• Stochastic Modeling
• Rainfall
• Runoff
• Civil and Environmental Engineering

Language dc:language

English

Repository record dc:identifier

https://scholarsarchive.byu.edu/etd/19

OAI identifier oai:identifier

oai:scholarsarchive.byu.edu:etd-1018