Graduation Year

2020

Document Type

Thesis

Degree

M.S.C.E.

Degree Name

MS in Civil Engineering (M.S.C.E.)

Degree Granting Department

Civil and Environmental Engineering

Major Professor

Mauricio E. Arias, Ph.D.

Committee Member

Mark Ross, Ph.D.

Committee Member

Sergio Alvarez, Ph.D.

Keywords

Crop Damage, Floodplain Management, Geospatial Information Systems, Natural Disaster, Risk Management

Abstract

Flooding is the most costly type of natural disaster, as well as the most frequent. To provide risk-based flood insurance, providers such as FEMA must be able to accurately determine an asset’s risk of flooding. Additionally, after a flooding event, providers need to quickly determine the direct damages that occurred to verify insurance claims and provide assistance to the affected communities. Many current approaches to flood risk and flood damage estimation involve the use of data or statistical extrapolation that can add various sources of uncertainty into the final damage estimate. In order to reduce uncertainties in flood risk analyses, the objective of this research is to outline an approach to flood damage estimation that can be conducted on a statewide scale while still estimating flood risk and damage on a structure-by-structure basis. This approach uses the observed flooding extent during and after Hurricane Irma, which was extracted from a collection of satellite images of the course of eight days. Asset exposure estimates come from two sources: a dataset of remotely-sensed building shapes determines a structure’s location in respect to the flood hazard, while multiple datasets of parcel data for each county within the state of Florida offer estimated values for the structures. The flood damage estimate was then applied to agricultural crops within Florida to determine any economic damages that may have occurred. The results of this analysis show that residential structures had the largest exposure to flooding during Hurricane Irma, with estimates ranging from $300 million to $2 billion per county, for the three counties that were studied in-depth. For agricultural crops, fruit crops were estimated to have a potential at-risk revenue of $38.2 million, with most of that coming from citrus crops. Vegetables were estimated to have a much higher value at risk, with a total of $940 million across all vegetable crops and $534 million of that coming from tomatoes. With improvements in the data used, this approach can offer a quick and accurate assessment of flood damages directly after a flood hazard, which would reduce the recovery time and economic impacts to the affected communities.

Download

Share

COinS