University of South Florida Scholar Commons Graduate Theses and Dissertations Graduate School June 2020 Structural and Agricultural Value at Risk in Florida from Flooding during Hurricane Irma Alexander J. Miller University of South Florida Follow this and additional works at: https://scholarcommons.edu/etd Part of the Civil Engineering Commons, and the Water Resource Management Commons Scholar Commons Citation Miller, Alexander J., "Structural and Agricultural Value at Risk in Florida from Flooding during Hurricane Irma" (2020). Graduate Theses and Dissertations.edu/etd/8257 This Thesis is brought to you for free and open access by the Graduate School at Scholar Commons. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Scholar Commons.
For more information, please contact scholarcommons@usf. Structural and Agricultural Value at Risk in Florida from Flooding during Hurricane Irma by Alexander J. Miller A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Civil Engineering Department of Civil and Environmental Engineering College of Engineering University of South Florida Major Professor: Mauricio E. Mark Ross, Ph.
Sergio Alvarez, Ph. Date of Approval: June 19, 2020 Keywords: Natural Disaster, Crop Damage, Risk Management, Geospatial Information Systems, Floodplain Management Copyright © 2020, Alexander J. Miller Dedication I dedicate this thesis to my sister, for keeping me on my toes; my brother, for keeping me humble; and my mother, for keeping me happy. Acknowledgments I would like to pay special recognition to my main thesis advisor, Mauricio, for putting up with me through all my theses.
This thesis could not have been done without the help of my entire thesis committee, for guiding me through this research, or for my employer and all of the mentors I have known at HDR Engineering. Table of Contents List of Figures .iii Chapter 1: Introduction. 1 Chapter 2: Literature Review .1 Natural Disasters and Flood Risks in the United States .2 Purpose for Flood Risk Estimations .3 Current Approaches to Estimating Flood Risk .4 Uncertainty in Flood Damage Estimations .5 Existing Research Gaps .1 Hurricane Irma Flooding Extent (raster feature): .2 Parcel Data by County (polygon feature): .3 Geospatial Analysis Process .1 Initial Spatial Analysis .2 Floodwater Depth Estimation Tool (FwDET) .3 Assigning Depth Values to Flooded Features .1 Flooding Extent and Depth .3 Ornamental and Nursery Crops .3 Palm Beach County. 44 i List of Figures Figure 1: Florida Counties Eligible for FEMA Assistance.
13 Figure 2: Hurricane Irma Multi-Sensor Precipitation Estimates. 14 Figure 3: Hurricane Irma Flooding Detection Raster with histogram of flood detection percentages. 15 Figure 4: Aerial footprints used to develop the Hurricane Irma Flooding Detection Raster. 16 Figure 5: Geospatial Analysis Process to Identify Flooded Crops and Buildings.
18 Figure 6: Geospatial Analysis Process to Identify Flood Depth Reaching Crops and Buildings. 20 Figure 7: Flooding Depth Raster from Hurricane Irma. 23 Figure 8: Crop flooding extent due to Hurricane Irma. 24 Figure 9: Inundated Area of Agricultural Land by Crop Category.
25 Figure 10: Inundated Area and Average Flooded Depth by Fruit Category. 26 Figure 11: Total Fruit Crop Revenue at Risk by Fruit Category. 26 Figure 12: Inundated Area and Average Flooded Depth by Vegetable Category. 29 Figure 13: Total Vegetable Crop Revenue at Risk by Vegetable Category.
29 Figure 14: Inundated Area and Average Flooded Depth by Ornamental Category. 30 Figure 15: Total Ornamental or Nursery Crop Revenue at Risk by Crop Category. 31 Figure 16: Building flooding extent due to Hurricane Irma. 32 Figure 17: Duval County Parcels with Building Flooding.
33 Figure 18: Duval County Just Value at Risk of Flooding by Parcel Classification. 33 Figure 19: Lake County Parcels with Building Flooding. 35 Figure 20: Lake County Just Value at Risk of Flooding by Parcel Classification. 35 Figure 21: Palm Beach County Parcels with Building Flooding.
37 Figure 22: Palm Beach County Just Value at Risk of Flooding by Parcel Classification. 37 ii 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. iii Chapter 1: Introduction Flooding is both the most costly type of natural disaster, as well as one of the most frequent. Combined with damages caused by tropical cyclones, storm-related flooding is expected to cause an estimated $54 billion in economic damages to the United States’ economy annually, with $34 billion of that expected to come from the residential sector (CBO, 2019). Florida is the state most impacted by storm-related flooding.
Florida has the most federal flood insurance policies of any state with approximately $440 billion in coverage, which is over twice the coverage of the second most flood-prone state, Texas (FEMA, 2019). 2017 was one of the worst years on record in terms of economic damage caused by tropical cyclones and storm-related flooding, with three of the five most destructive storms of all time occurring during that same year (Smith and NOAA National Centers For Environmental Information, 2020). Operated by the Federal Emergency Management Agency (FEMA), the National Flood Insurance Program (NFIP) is the largest provider of flood insurance within the United States. To accurately and fairly assign insurance rates to policyholders, the NFIP conducts flood hazard analysis and mapping to determine the flood risk at each individual structure.
The standard approach to this flood risk estimation process involves first assessing the flood hazard extent and depth, which is typically done by extrapolating statistical riverine data for inland areas, or storm surge and wind data for coastal areas. These data are combined with physical topographic data and then a statistical model is used to estimate the resultant flooding extent and depth from a flood hazard of a certain probability. Additionally, a hydrologic model can be used to estimate discharge and depths in rivers that may result from a storm event of a certain probability, instead of using observed data (NRC, 2009). Once the hydraulic component of a flood hazard is determined, the exposure and vulnerability of each structure within this floodplain (the NFIP typically focuses on the 1.0% chance, or 100-year return period, flood event) must be determined.
The relationship between the depth of flooding experienced at a 1 structure and the economic damage that results is known as a depth-damage curve. These curves can be determined on a structure-by-structure basis, but more likely the curves are generalized for a specific structure type within a study region. Both the hydraulic and monetary components of these flood risk analyses can introduce large uncertainties in the final risk estimates depending on the type of data they use and how they use it (de Moel and Aerts, 2011). In one study, both the valuation of the structure at risk of flooding and the depth-damage curve used in the analysis were found to introduce a factor of 2 of uncertainty into the final flood damage estimate, with variations in the flooding depth estimation contributing an additional, lesser amount of uncertainty (de Moel and Aerts, 2011).
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 study focused on the exposure, or the value at risk of flooding, rather than actual damage values, since such analysis would require direct information from insurance claims. This approach uses the observed flooding extent during and after Hurricane Irma extracted from a collection of satellite images over the course of eight days. This observed flooding extent data removes common sources of uncertainty that come from statistical extrapolation and modeling of a flood hazard of a certain probability.
Structure exposure estimates come from two sources: a dataset of remotely-sensed building shapes determines a structures location in respect to the flood hazard, while multiple datasets of parcel data for each county within the state of Florida offer exposure assessments and estimated values for the properties. The Hurricane Irma flooding extent imagery does not offer any information on the depth experienced at a certain location; therefore, a recent geospatial tool called the Floodwater Depth Estimation Tool (FwDETv2) (Cohen et al., 2019) was used with a 30-meter resolution topographic dataset for the entire state of Florida to estimate the flooding depth experienced at any location within the state. The flooding depth from Hurricane Irma produced using this tool was then applied to all agricultural crops within the state to determine any economic damages that may have occurred during the flooding. The research presented in this thesis aims to answer the following research questions: 1.
What value of agricultural crops in Florida were at risk of flooding due to Hurricane Irma? 2 2. What value of buildings in Florida were at risk of flooding due to Hurricane Irma? 3. How does this process and damage estimation compare to other flood risk estimation techniques? The outline of this thesis is as follows: Chapter 2 provides a review of recent literature involving natural disasters within the state of Florida and the flood hazard risk assessments that are commonly done to prepare for them; Chapter 3 outlines the methodology and data used in this research’s approach to estimating the flood damage caused by Hurricane Irma; Chapter 4 presents the results of this analysis, both at the state level and a more detailed analysis for three counties; Chapter 5 discusses the importance of these results and compares them to other flood risk estimations; and finally, Chapter 6 offers an overview of the research and results of this thesis, as well as implications for management and future research. 3 Chapter 2: Literature Review 2.1 Natural Disasters and Flood Risks in the United States Natural disasters affecting Florida and the southeastern United States, which include floods, hurricanes, and tornados, can cause significant economic impacts for a government and its citizens.
Larger disasters can slow local economic growth for decades after the event (Flowers, 2018).