<%BANNER%>

GIS-Based Future Land Use Hurricane Storm Surge Hazard Analysis

Permanent Link: http://ufdc.ufl.edu/UFE0043830/00001

Material Information

Title: GIS-Based Future Land Use Hurricane Storm Surge Hazard Analysis a Case Study for Volusia County, Florida
Physical Description: 1 online resource (76 p.)
Language: english
Creator: Zou, Yuyang
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2011

Subjects

Subjects / Keywords: analysis -- gis -- hazard -- hazus-mh -- lu -- slr
Urban and Regional Planning -- Dissertations, Academic -- UF
Genre: Urban and Regional Planning thesis, M.A.U.R.P.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: In recent years, the damage caused by the hazards of flooding has increased in Florida. That increase may be the result of many factors but paramount among those factors is the continued development of urban land use within flood damage areas adjacent to the Florida coastline. Planners with their role as protectors of public health and safety must work with emergency managers to develop and implement disaster plans, mitigation plans and to assist with disaster response activities. The objective of this thesis is to explore a methodology to understand the implication of hurricane hazard analysis for future land use planning in coastal areas of Florida in an attempt to answer the following questions. First, how do we best implement quantitative hurricane hazard models for future land use decision making in coastal Florida? Next, will a quantitative hurricane hazard model (HAZUS-MH) integrated with a future land use model be helpful for planning in coastal Florida? Finally, how do we quantify the effects of sea level rise using hurricane hazard models for future land use planning? To answer these questions, an approach using storm surge (SS) models by HAZUS-MH that incorporate the presence or absence of a 1.5 meter (approximately 4.9 feet) sea level rise was developed and three projected scenarios are created for further analysis. Volusia County, Florida is selected as a case study. The study results show a number of parcels that would be lost in certain land use categories. Tables are generated indicating the current assessed market value for parcels inundated by the scenarios. More stress caused by sea level rise according to the result of Alternative Scenario II shows, that the coastline would be retracted by losing large amounts of land. This research is not intended to specifically represent the inundation risk due to a probabilistic 100-year SS and sea level rise for any specific building or land parcel. However, this is a good indication for what may occur. The methodology could also be used as a supplementary for forecasting economic analysis and future land use planning or county resilience planning.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Yuyang Zou.
Thesis: Thesis (M.A.U.R.P.)--University of Florida, 2011.
Local: Adviser: Zwick, Paul D.
Local: Co-adviser: Jourdan, Dawn.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2013-12-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2011
System ID: UFE0043830:00001

Permanent Link: http://ufdc.ufl.edu/UFE0043830/00001

Material Information

Title: GIS-Based Future Land Use Hurricane Storm Surge Hazard Analysis a Case Study for Volusia County, Florida
Physical Description: 1 online resource (76 p.)
Language: english
Creator: Zou, Yuyang
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2011

Subjects

Subjects / Keywords: analysis -- gis -- hazard -- hazus-mh -- lu -- slr
Urban and Regional Planning -- Dissertations, Academic -- UF
Genre: Urban and Regional Planning thesis, M.A.U.R.P.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: In recent years, the damage caused by the hazards of flooding has increased in Florida. That increase may be the result of many factors but paramount among those factors is the continued development of urban land use within flood damage areas adjacent to the Florida coastline. Planners with their role as protectors of public health and safety must work with emergency managers to develop and implement disaster plans, mitigation plans and to assist with disaster response activities. The objective of this thesis is to explore a methodology to understand the implication of hurricane hazard analysis for future land use planning in coastal areas of Florida in an attempt to answer the following questions. First, how do we best implement quantitative hurricane hazard models for future land use decision making in coastal Florida? Next, will a quantitative hurricane hazard model (HAZUS-MH) integrated with a future land use model be helpful for planning in coastal Florida? Finally, how do we quantify the effects of sea level rise using hurricane hazard models for future land use planning? To answer these questions, an approach using storm surge (SS) models by HAZUS-MH that incorporate the presence or absence of a 1.5 meter (approximately 4.9 feet) sea level rise was developed and three projected scenarios are created for further analysis. Volusia County, Florida is selected as a case study. The study results show a number of parcels that would be lost in certain land use categories. Tables are generated indicating the current assessed market value for parcels inundated by the scenarios. More stress caused by sea level rise according to the result of Alternative Scenario II shows, that the coastline would be retracted by losing large amounts of land. This research is not intended to specifically represent the inundation risk due to a probabilistic 100-year SS and sea level rise for any specific building or land parcel. However, this is a good indication for what may occur. The methodology could also be used as a supplementary for forecasting economic analysis and future land use planning or county resilience planning.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Yuyang Zou.
Thesis: Thesis (M.A.U.R.P.)--University of Florida, 2011.
Local: Adviser: Zwick, Paul D.
Local: Co-adviser: Jourdan, Dawn.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2013-12-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2011
System ID: UFE0043830:00001


This item has the following downloads:


Full Text

PAGE 1

1 GIS BASED FUTURE LAND USE HURRICANE STORM SURGE HAZARD ANALYSIS: A CASE STUDY FOR VOLUSIA COUNTY, FLORIDA By YUYANG ZOU A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS IN URBAN AND REGIONAL PLANNING UNIVERSITY OF FLORIDA 2011

PAGE 2

2 2011 Yuyang Zou

PAGE 3

3 To my d earest f amily and f riends

PAGE 4

4 ACKNOWLEDGMENTS I would like to show the deepest and most grateful appreciation to m y parents for their endless support. I also would like to express my sincere thanks to my committee members Dr. Paul Zwick and Dr. Dawn Jourdan. I am greatly indebted to my advisor and committee chair Dr. Paul Zwick, for his support, guidance and encourag ement all the time. I thank my committee co chair Dr. Jourdan who was also my professor mentor when I first came here, a complete new place from my home country China, fo r her passion, patience, advice and support during my study here. Many thanks to my d earest LUCIS group members, Dr. Abdulnaser Arafat and Elizabeth Thompson for their technical support constructive criticism of my work and companionship back up. Special thanks should go to the entire lovely c olleague s from the Shimberg Center for Housin g Studies at the University of Florida for their care and support. Finally, I would like to thank all my friends that without you I could never get this far.

PAGE 5

5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURES ................................ ................................ ................................ .......... 8 LIST OF ABBREVIATIONS ................................ ................................ ........................... 10 ABSTRACT ................................ ................................ ................................ ................... 11 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 13 Overview ................................ ................................ ................................ ................. 13 Study Area ................................ ................................ ................................ .............. 13 Study Objectives ................................ ................................ ................................ ..... 15 2 LITERATURE REVIEW ................................ ................................ .......................... 16 HAZUS MH Model ................................ ................................ ................................ .. 16 Overview ................................ ................................ ................................ .......... 16 Coastal Flood Hazard Modeling ................................ ................................ ....... 19 Flood Insurance Study ................................ ................................ ..................... 20 Depth Damage Curves and Functions ................................ ................................ .... 20 Depth Frequency Curve ................................ ................................ ................... 20 Depth Damage Functions ................................ ................................ ................. 21 The Definition of Vulnerability ................................ ................................ ........... 23 The Case Study with GIS Anal ysis in Floridas Coastal Area ................................ 24 Theories and Research on Sea Level Rise ................................ ............................. 24 3 DATA AND METHODOLOGY ................................ ................................ ................ 26 Data ................................ ................................ ................................ ........................ 26 Census 2000 ................................ ................................ ................................ .... 26 Property Tax Parcel Data ................................ ................................ ................. 26 DEM (Digital Elevation Model) ................................ ................................ .......... 26 Methodology Overview ................................ ................................ ........................... 27 Base Scenario ................................ ................................ ................................ ........ 29 Alternative Scenario I ................................ ................................ .............................. 34 Step One ................................ ................................ ................................ .......... 34 Step Two ................................ ................................ ................................ .......... 34 Step Three ................................ ................................ ................................ ........ 36 Step Four ................................ ................................ ................................ .......... 36

PAGE 6

6 Alternative Scenario II ................................ ................................ ............................. 36 4 FINDINGS AND RESULTS ................................ ................................ ..................... 38 Base Scenario ................................ ................................ ................................ ........ 38 Alternative Scenarios ................................ ................................ .............................. 38 Define Building Loss ................................ ................................ ......................... 39 Comparison: Alternative Scenario I Base Scenario ................................ ........ 39 Comparison: Alternative Scenario I Alternative Scenario II ............................ 40 Alternative scenario I: 100 yr storm surge ................................ .................. 4 7 Alternative scenario II: 100 yr storm surge and a 1. 5m sea level rise ........ 49 5 DISCUSSION ................................ ................................ ................................ ......... 56 Discussion of Findings and Methods ................................ ................................ ...... 56 Future Research Opportunities ................................ ................................ ............... 57 6 CONCLUSION ................................ ................................ ................................ ........ 59 APPENDIX A VOLUSIA 100 YR COASTAL FLOOD EVENT SUMMARY REPORT .................... 62 B VOLUSIA 100 YR COASTAL FLOOD EVENT QUICK ASSESSMENT REPORT .. 73 LIST OF REFERENCES ................................ ................................ ............................... 74 BIOGRAPHICAL SKETCH ................................ ................................ ............................ 76

PAGE 7

7 LIST OF TABLES Table page 1 1 Projections of population Volusia vs. Florida ................................ ................... 14 4 1 Parameters for depth damage equitation for estimating building losses ............ 39 4 2 Total building damage due to 100 yr SS by year 2010 parcel, Volusia, Flori da (thousand dollars) ................................ ................................ ............................... 40 4 3 Total Building damage due to 100 yr SS and 1.5m SLR by 2010 Parcel, Volusia, Florida (thousand dollars) ................................ ................................ ..... 41 4 4 Original table by depth, loss and land use type for 100 yr storm surge (thousand dollars) ................................ ................................ ............................... 47 4 5 Normalized table by depth, loss and land use type for 100 yr storm surge ........ 48 4 6 Normalized table by depth, loss and land use type for 100 yr storm surge and a 1.5m sea level rise (thousand dollars) ................................ ...................... 49 4 7 Norma lized table by depth, loss and land use type for 100 yr storm surge and 1.5m sea level rise ................................ ................................ .............................. 50 4 8 Controlled building damage between WS/WO SLR by 2010 parcel, inundation between 0 1ft (thou sand dollars) ................................ ..................... 51 4 9 Controlled building damage between WS/WO SLR by 2010 parcel, inundation between1 4ft (thousand dollars) ................................ ...................... 52 4 10 Controlled building damage between WS/WO SLR by 2010 parcel, inundation between 4 8ft (thousand dollars) ................................ ...................... 53 4 11 Controlled building damage between WS/WO SLR by 2010 parcel, inundation between 8 12ft (thousand dollars) ................................ .................... 54 4 1 2 Controlled building damage between WS/WO SLR by 2010 parcel, inundation above 12ft ................................ ................................ ......................... 55

PAGE 8

8 LIST OF FIGURES Figure pag e 1 1 Study area location of Volusia County ................................ ................................ 14 2 1 Create study region ................................ ................................ ............................ 17 2 2 Define flood hazard type ................................ ................................ ..................... 18 2 3 Steps in acquiring users data ................................ ................................ ............. 19 2 4 General model of structure depth da mage function.(Willett, 1996) ..................... 22 3 1 Diagram of study methodology. ................................ ................................ .......... 28 3 2 Overview of HAZUS MH coastal flood hazard modeling pro cess ....................... 29 3 3 Create Volusia County study region ................................ ................................ ... 30 3 4 Shoreline characteristic inputs ................................ ................................ ............ 31 3 5 Hazard model analysis type and cell size ................................ ........................... 31 3 6 The delineated floodplain by coastal flood hazard modeling .............................. 32 3 7 Base Scenario of 100 yr storm surge hazard, Volusia County, Florida .............. 33 3 8 Flowcharts for steps of GIS methodology ................................ ........................... 35 4 1 Land use map for Alternative Scenario I of SS hazard, Volusia, Florida ............ 42 4 2 Land Use Map for Alternative Scenario II of SS and a 1.5M SLR hazard, Volusia, Florida ................................ ................................ ................................ ... 43 4 3 Inundation depth map for Alternative Scenario I of SS hazard, Volusia, Florida ................................ ................................ ................................ ................ 44 4 4 Inundation depth map for Alternative Scenario II of 1 00 yr SS and a 1.5m SLR hazard, Volusia, Florida ................................ ................................ .............. 45 4 5 Pie Charts for total percentage losses of building damage by 100 yr SS, Volusia, Florida ................................ ................................ ................................ ... 46 4 6 Pie Charts for total percentage losses of building damage by 100 yr SS and 1.5m SLR, Volusia, Florida ................................ ................................ ................. 46 4 7 Building Loss by different land use type in the function of inundation depth for 100yr storm surge ................................ ................................ ............................... 47

PAGE 9

9 4 8 Building Loss Normalized by different land use type in the function of inundation depth for 100yr storm surge ................................ .............................. 48 4 9 Building Loss by different land use type in the function of inundation depth for 100yr Storm Surge and a 1.5m sea level rise ................................ ..................... 49 4 10 Building Loss Normalize d by different land use type in the function of inundation depth for 100yr storm surge and a 1.5m sea level rise ..................... 50

PAGE 10

10 LIST OF ABBREVIATION S BEBR Bureau of Economic and Business Research at University o f Florida CDMS Comprehensive Data Management System DEM Digital Elevation Model DOR Department of Revenue ESRI Environmental Systems Research Institute FDOR Florida Department of Revenue FEM A Federal Emergency Management Agency FGDL Florida Geographic D ata Library FIS Flood Insurance Study GIS Geographic Inf ormation System SLR Sea Level Rise SS Storm Surge SWEL Still Water Elevation USACE United States Army Corps of Engineers USGS United States Geological Survey

PAGE 11

11 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Arts in Urban and Regional Planning GIS BASED FUTURE LAND USE HU RRICANE STORM SURGE HAZARD ANALYSIS: A CASE STUDY FOR VOLUSIA COUNTY, FLORIDA By Yuyang Zou December 2011 Chair: Paul Zwick Cochair: Dawn Jourdan Major: Urban and Regional Planning In recent years, the damage caused by the hazards of flooding has increa sed in Florida. That increase may be the result of many factors but paramount among those factors is the continued development of urban land use within flood damage areas adjacent to the Florida coastline. Planners with their role as protectors of public h ealth and safety must work with emergency managers to develop and implement disaster plans, mitigation plans and to assist with disaster response activities. The objective of this thesis is to explore a methodology to understand the implication of hurrica ne hazard analysis for future land use planning in coastal areas of Florida in an attempt to answer the following questions. First, h ow do we best implemen t quantitative hurricane hazard models for future land use d ecision making in coastal Florida? Next, will a quantitative hurricane haz ard model (HAZUS MH) integrated with a future land use model be helpful for planning in coastal Florida? Finally, how do we quantify the effects of sea le vel rise using hurricane hazard model s for future land use planning? To answer these questions, an approach using storm surge (SS) models by HAZUS MH that incorporate the presence or abse n ce of a 1.5 meter (approximately 4.9

PAGE 12

12 feet) sea level rise was developed and three projected scenarios are created for further analysis. V olusia County, Florida is selected as a case study. The study results show a number of parcels that would be lost in certain land use categories. Tables are generated indicating the current assessed market value for parcels inundated by the scenarios. More stress caused by sea level rise according to the re sult of Alternative Scenario II shows that the coastline would be retracted by losing large amount s of land. This research is not intended to specifically represent the inundation risk due to a probabili stic 100 year SS and sea level rise for any specific building or land parcel However, this is a good indication for what may occur. The methodology could also be used as a supplementary for forecasting economic analysis and future land use planning or cou nty resilience planning.

PAGE 13

13 CHAPTER 1 INTRODUCTION Overview One of the components related to the study of natural hazards is the recognition of land use vulnerability. With an understanding that certain land use categories are more vulnerable to natural haz ards, planners could make better development decisions based on the knowledge of the future impacts caused by those hazards. As a result, HAZUS MH models are widely accepted and applied by disaster management researchers, and should be employed to a great er extent by urban and regional planners. With the application of the model, the long term impacts of SS and sea level rise on infrastructures, property parcels, and other public and private resources could be visualized. And this could help local governme nts to think seriously about if the development i n the certain coastal areas is valuable and the appropriate property tax increasing with the worry about the liability associated with those future limitations. Study Area Volusia County is located on the northeast coast of the state of Florida (Figure 1 1) The County lies on the coastline by the Atlantic Ocean. Coastal areas are particularly vulnerable to several of nature hazards, such as hurricanes, tropical storms, flooding, and sea level rise, etc. Th ese natur al hazard s would threat en the safety of coastal residents and would cause damage s and the loss of both public and private properties According to Year 2010 property tax parcel data provided by Florida Department of Revenue (FDOR) and updated in F lorida Geographic D ata Library (FGDL) in February 2011 Volusia County covers an area of 759 743 acres a mong which 172 734 acres are residential land

PAGE 14

14 Figure 1 1 S tudy area location of Volusia County According to the research of bureau of economic and business research at University o f Florida ( BEBR ), Volusia County comprises approximately 3% of the state of Floridas population. Their medium projection of population growth in Volusia County increases every decade by 55,330 people (Table 1 1) Table 1 1 Projections of p opulation Volusia vs. Florida Year Volusia Florida CENSUS 2000 443,343 15,982,824 PROJECTIONS(Medium) 2010 510,300 18,881,400 2020 565,600 21,417,500 2030 620,900 23,979,000

PAGE 15

1 5 Study Objectives The purpose of this study is to exami ne the GIS based hurricane hazard analysis model (HAZUS MH), to assess if it is helpful for enhancing future land use planning in Florida coastal areas. The study includes three parts. First, a base los s will be estimated by incorporating 2000 Census data with a flood hazard model within HAZUS MH Second, since HAZUS MH uses estimation s based on Census 2000 data rather than actual land use property parcel data, 2010 land use parcel data will be introduced to see how different between the results generated b y HAZUS MH and the results obtained using parcel data The last part is to incorporate the same flood hazard model with a 1.5 meter sea level rise and 2010 land use parcel data to see how much of the county is affected and to inspect the increased damage due to the sea level rise. Three projected scenarios are created as follow s : (1) Base Scenario by HAZUS MH with its default 2000 Census d ata, (2) Alternative Scenario I: Base scenario by HAZUS MH and 2010 l and use parcel data, (3) Alternative Scenario II: incorporate s Alternative Scenario I with a 1.5 meter sea level rise

PAGE 16

16 CHAPTER 2 LITERATURE REVIEW HAZUS MH Model Overview The Hazards U.S. Multi Hazard (HAZUS MH) was developed by the Federal Emergency Management Agency (FEMA) with state of the art geog raphic information system s (GIS) as its running platform in S prin g 2004 (FEMA,2011) The application includes models of flood, hurricane (wind), and e arthquake. HAZUS MH model s produce loss estimates in planning for multiple hazards risk mitigation, emerge ncy preparedness, response and recovery. The estimation methodology adopted in HAZUS MH deals with a wide rang e of different types of losses. The HAZUS MH flood model is aimed at help ing with decision making in certain areas that are prone to flooding risk It is a state of the art analysis for identifying an d quantifying risks by flood hazard and loss estimation. The analysis includes three levels. HAZUS MH model L evel 1 is based on default data provided with the software and the most updated default inven tory data is based on Census 2000. To accomplish this level requires minimum technical knowledge other than knowing about basic analytical method s with GIS The loss estimation through L evel1 is due to depth of flooding. Level 2 is improved by inputting mo re relevant parameter s which meet all the methodology used in the Level 1. Level 3, the most de tailed data analysis, requires more advanced information and measurement of the flood. The methodology to finish the data acqui sition might be newer and more acc urate by experts and engineers who are

PAGE 17

17 required to put extensive effort int o the process. Much more time is therefore needed to sum up and prove results compared to previous L evel1 and Level 2 (FEMA, 2011) The Major st eps for Level 1 analysis in the HAZU S MH flood model are described below. Figure 2 1. Create study region

PAGE 18

18 1. Define the study region with hazard type. The hazards to be investigated are determined in this st age with no restriction on the amount of hazard types at a time However once the stu dy region with certain hazard is built, no other hazard type can be add ed in. other than create another new region ( Figure 2 1) 2. Input Inventory data The HAZUS MH flood model includes two type s of flooding models a c oastal and a r iverine model Before inv entory data is inputted, the type of the flood hazard is determined according to the characteristic of the study area. Figu re 2 2 Define flood hazard type The user data, in terms of the regional DEM data is downloaded from the United States Geological Survey ( USGS ) web site.

PAGE 19

19 Figure 2 3 Steps in acquiring users data 3. Damage estimations, which include direct and induced damage 4. Losses estimations, which inclu de social and economic losses (Sour ce : Adapted from HAZUS MH flood user manual ) Coastal Flood H azard Modeling Coas tal flood hazards are calculated by HAZUS MH and it requires the user to define certain information according to each specific county. The required inputs are list ed below: Study region Shorelines Wave exposure Shore type 100 yr Flood St illwater Elevation (SWEL) 100 yr wave set up which might be given in Flood Insurance Study Report (FIS) Coastal flood return period For the rest of the data, the coastal model will default to the users inputs. (Sou rce : Adapted from HAZUS MH flood technic al manual )

PAGE 20

20 Flood Insurance Study This FIS report is provided by FEMA with the aim of help ing local and regional planners to further promote land use and floodplain development. According to the report for Volusia County, Florida the 1 percent Annual Chan ce Stillwater elevation for the Atlantic Ocean is not revised which is 6.9 feet using the North American Vertical Datum of 1988(NAVD88) as the referenced vertical datum. At the same time, the 1 Percent Annual Chance Stillwater Elevations for the open are a along the Atlantic Ocean were not modified to include the effects of wave setup (FEM A, 2011) which indicates that wave setup was not a necessary input for the coastal flood model by HAZUS MH for Volusia County. Depth Damage Curves and Functions Depth is usually the primary parameter when estimating the damages due to flood. Depth Frequen cy Curve Depth frequency curve represents the relation ship between the depth of flooding and the annual chance of inundation greater than the depth. The methodology adopted in HAZUS to estimate the direct economic losses is based on this curve compiled fr om a variety of sources including the Federal Insurance and Mitigation Administration (FIMA) credibility weighted depth damage curves, and selected curves developed by the U.S. Army Corps of Engineers (USACE), and the USACE Institute for Water Resources (USACEIWR) ( FEMA, 2011 ) The frequency of flood hazard varies over time measuring the risk of it occurring is difficult to predict. Also, flood hazard represent s only one type of sources of natural hazards For example, t he flood hazard may be that an area is inundated about once every 10 0 years by the risk of storm surge or it may be that an area is subject to flood

PAGE 21

21 depths ranging from 0. 5 to 1 .5 meters Flood frequency curves define flood hazard by showing the relation ship between depth of flooding and th e annual chance of inundation greater than that depth of flooding in the particular year. ( F EMA, 2011 ) (Titu s, 2001) Depth Damage Functions The methodology of the HAZUS MH flood model for es timating direct physical damage, such as the repair cost, replacement cost etc. to the general building stock is relatively straightforward and easy to understand and to ap ply in the models Usually, f or a given Census 2000 block, each occupancy type of the construction has an appropriate damage function assigned to it For instance, functions may vary for a one story building without basement and a one story building with b asement Different inundation depths leading to different extent s of flooding are used to determine the associated percent age damage of the buildings and constructions Generally, t his percent age damage is multiplied by the replacement value to produce an estimate of total dollar loss. Conceptually, a 1 10% damage is considered to be a slight loss, a 11 50% damage is considered to be moderate loss, and more than 50% damage is considered as substantial loss ( F EMA, 2011) (Davis, 1985) Deta iled contents damag e functions are applied within different cases all over the US by the USACE For example in New Orleans District a number of structures without basements were reviewed to form the exact functions for this area by two categories which are one story and tw o story buildings A 5 f eet water depth indicates a substantial loss of its maximum to a one story building, while it could be less for a two story building at the water level of 5 feet. In this particular function, a 14 feet water depth results in the sub stantial loss of its maximum to a two story building in that area ( F EMA, 2011) (Davis, 1985)

PAGE 22

22 For all the functions, due to limited claims data, it is assumed that a ll depth damage curves developed by the USACE represent structures with no basement for Atla ntic coastal area ( FEMA, 2011). In Willett and Kiefers research, (Willet, 1996) hypothetical damages were obtained for several levels of flooding depth, which are 0 to 1 feet, 1 to 4 feet, 4 to 8 feet, 8 to 12 feet, and above 12 feet. A series of linear m odels were tested and a structure damage equation was generated from the models to estimate the loss percentage of the structures. The equation could be applied to buildings with and without basement s The expression for building with basement is simplifie d as: % structure damage = And t he expression for building s without basement s is simplified as: % structure damage = Figure 2 4 General model of structure depth damage function (Willett, 1996)

PAGE 23

23 Figure 2 4 shows the plotted results of damage functions of both with basement and with no baseme nt. The damage increased fast when inundation depth was below 4 feet for both condition s The percentages of damages were gradually level off at the inundation depth around 12 feet for both situations. The D efinition o f V ulnerability Climate Change 2007, t he fourth assessment report from Intergovernmental Panel on Climate Change has noted that The term vulnerability may therefore refer to the vulnerable system itself (IPCC, 2007) (Matisziw, 2011) To be more specific, Disaster proneness and insufficient capability (Pin kowaski, 2008,) are two main concerns for researchers and scholars to investigate in for the vulnerability cause d by hurricane. The former is examined by the physic al condition of an area according to its topography (Simpson, 1998) For instance, coastal cities are more sensitive than inland cities which are why some scholars note that most of Florida s coastal residents are prone to disaster caused by hurricane (Pinkowski, 2008). The latter is of more concerned to geographers, ecologists, economists, human ist as well as urban planners where the post effects of hurricanes which exceed the capability of an area t o adapt itself to the situation (Puszkin, et al. 2006) (McLeod, et al., 2010). Seven criteria used to define main vulnera bilities are (IPCC, 2007) : magnitude of impacts, timing of impacts, persistence and reversibility of impacts, likelihood (estimates of uncertainty) of impacts and vulnerabilities, and confidence in those estimates, potential for adaptation,

PAGE 24

24 distributional aspects of impac ts and vulnerabilities, Importance of the system(s) at risk. The Case Study with GIS Analysis in Floridas Coastal Area In Murley Chevlin and Esnard s research (Murley 2004 ) three coastal Florida counties, Martin, St. Lucie and Indian River ar e selected as the study area. The researcher mapped old and new geographic delineations for the study area. Also the amount of land and number of parcels we re compared aim ing to find out the difference between tax parcels and land acres and the relation sh ip between the existing acreage of land parcels and the number of improved real estate assets on a certain parcel of land. Theories and Research o n Sea Level Rise Sea level rise not only could make an area of coastal land inundated and increase coastal ero sion, but it could also makes events such as tsunamis, storm surges and other marine hazards more likely to occur causing flooding and saltwater intrusion which could result in greater loss (Oliver, 2010) (Darwin, 2001) Sea level rise issues threaten most of the U.S. coast areas The entire Atlantic Coast is subsiding. According to Vivien s research, an area of 89.0% of the Atlantic Coast region are affected by varies of rates of sea level rise exceeding 2 m m/yr (Vivien, 1991) Nearly half of the Gulf Coast is eroding, with 40% retreating at rates greater than 2 m m/yr. The Gulf Coast west of the Florida Panhandle displays the highest rates of relative sea level rise in the U.S. Sea level trends over the perio d 1931 1988 had an average value of 8.1 mm/yr ( Cushman, et al., 1991 ) (Nicholls,1999) An estimation of a global sea level rise that provided by t he International Panel on Climate Change (IPCC) was between 0.6 and 2

PAGE 25

25 feet (0.18 to 0.59 meters) in the next c entury ( IPCC, 2007 ). The c limate change should be the one of the main reasons that caused sea level rise The effects of the global sea level rise in the coastal areas will be spatially non uniform The impacts of this accelerated sea level rise (SLR) are replete with gloom which include shoreline retreat, mainland inundation, sal twater intrusion, inland population density increasing shortage of fresh water resource s and agric ultural lands (McLeod, 2010) Certain areas of coastal zone s will be permanently inundated to a depth equivalent to the vertical rise in sea level. Meanwhile, episodic flooding from storm surges could penetrate much further inland. Beaches and coastal stru ctures are threatened without doubt. I ncreasing salinization caused by sea level rise could pollute drinking water supplies and be extremely harmful to crops and soil of agriculture land (Cushman, et al., 1991)

PAGE 26

26 CHAPTER 3 DATA AND METHODOLOGY Data Census 2000 Census 2000 represents the 22nd US census by the US Census Bureau conducted in April 1st, 2000 ( http://en.wikipedia.org/wiki/Census_2000 ) A Census block is the smallest geographic unit used by the US Census Bureau to generate all housing information with in a region This suggests the data might be the most complete at the time but i s an aver age value. HAZUS MH has adopted Census 2000 as the basis inventory data for hazards analysis. Property Tax Parcel Data The parcel data shapefile needed for analysi s are retrieved from the Florida Geographic Digital Library (FGDL) which is Year 2010 tax parcel data updated in March 2010. The parcel data is used for Volusia County, Florida for the case study. All the tax parcel data have the following hor izontal coord inate system and no projections are needed. The source descriptions are listed below. Projected coordinate system name: Albers Conical Equal Area Geographic coordinate system name: GCS_North_American_1983_HARN Linear Units: meter DEM (Digital Elevation Mo del) The U.S. Geological Survey (USGS) produces a digital elevation mod el (DEM) from terrain data. DEM represents only the height information. The grid cells of a DEM raster data are equal sized. H AZUS MH uses the 1 degree DEM from USGS with the source des cription s listed below. Coordinate system name: Albers Conical Equal Area

PAGE 27

27 Datum: D_ North_Amarican_ 1983 Angular Units: Degree The HAZUS MH model developed for this thesis is implemented in Arc View 9.3.1 the geographic information systems ( GIS ) software pa ckage released by the Environmental Systems Research Institute (ESRI). Methodology Overview The purpose of this study wa s to examine the GIS based hurricane hazard analysis model (HAZUS MH), and to assess if it is helpful for enhancing future land use plan ning in Florida coastal areas. The study include d three parts. First, a base los s would be estimated by incorporating Census 2000 data with coastal flood hazard model. Second, since HAZUS MH has its estimation on Census 2000 data rather than actual land u se property parcel data, Year 2010 property land use parcel data would be introduced to examine how close the results generated by HAZUS MH were to those obtained with parcel data The last part was to incorporate the same storm surge (SS) model with a 1. 5 meter sea level rise (SLR) and Year 2010 land use parcel data to see how much of the county was influenced and understand the increased damage due to the sea level rise. Three projected scenarios were created as follows (1) The Base Scenario by HAZUS MH with its default Census 2000 Data, (2) Alternative Scenario I: Base scenario by HAZUS MH and Year 2010 Land use parcel data, (3) Alternative Scenario II: incorporate Alternative Scenario I with 1.5 meter SLR Figure 3 1 is a diagram of the research method ology used in this study that w ould be discussed in detail in the following sections of this chapter

PAGE 28

28 Figure 3 1 Diagram of study methodology.

PAGE 29

29 Base Scenario The base scenario is for storm surge hazard of Volusia County. It wa s generated by the coastal flood model with HAZUS MH. The objective of the base disaster scenario aim ed not only to examine the accuracy of the default data base in HAZUS MH model according to the summary report created during the modeling process, but also to obtain the 100 yr flood plain boundary as well as the related Digital Elevation Model for Volusia County This study estimate d the potential losses under a presumed ideal condition that no sea level rise occurred from the 100 yrs returned storm surge The modeling processes to d elineate floodplain by HAZUS MH are included in the Figure 3 2 below, as an overview. Figure 3 2 Overview of HAZUS MH coastal flood hazard modeling process (Source Adapted from HAZUS MH flood Technical manual) Certain GIS steps were taken as described b elow.

PAGE 30

30 Create a new region In HAZUS MH, a study region was created for Volusia County, Florida with a specified hazard type of flood, identified state and county names The HAZUS MH used its default database to generate the analysis ( Figure 3 3) Figure 3 3 Create Volusia County study region Defining the flood h azard Open ed th e study region in HAZUS MH, cho se flood hazard type on the Hazard menu by coastal only.

PAGE 31

31 Obtain ed data in the study region The regional DEM data wa s downloaded from USGS web site us ing the NAVD88 vertical datum and the DEM file should be feet for USGS NED data. Create d new scenario. The shoreline for Volusia County wa s selected for analysis using a default national shoreline which wa s delineated by county in HAZUS MH. The parameter s wer e full wave exposure and sandy beach, large dunes. According to the FIS Report for Volusia County, the still water elevation level ( SWEL ) was 6.9 feet using NAVD88 a s the reference vertical datum ( Figure 3 4 ) The Scenario report wa s named Ba se Scenar io which would be seen in the summary report as appendix A. Figure 3 4 S horeline characteristic inputs Figure 3 5. Hazard model analysis type and cell size

PAGE 32

32 Delineating f loodplain R a n coastal hazard analysis with 100yrs single return perio d type with default output cell size 27.15 ( Figure 3 5 ) Figure 3 6 The d elineated floodplain by coastal flood hazard modeling Volusia County Floodplain: Intersect ed the Volusia County boundary polygon and the floodplain boundary polygon directly generated by HAZU S MH ( Figure 3 6 ) The flooding region was an overall calculation with all varied criteria and exceeded the boundary of Volusia County ( Figure 3 7 ) Result report. HAZUS MH generate d a global summary report for the estimate d losses and quick assessment Report. See Appendix A and Appendix B.

PAGE 33

33 Figure 3 7 Base Scenario of 100 yr storm surge h azard, Volusia County, Florida

PAGE 34

34 Alternative Scenario I The Alternative Scenario I which was a storm surge only scenario, wa s originally from the Base Scenario inco rporating Year 2010 land use tax parcel data, obtained from Florida Geographic Digital Library (FGDL). HAZUS MH estimate d the loss by Census block with data from year 2000 which was obtained by averaging the percentage of the block filled by water. The met hodology adopted here wa s to create a storm surge ( SS ) polygon, which wa s based on the parcel polygon of Volusia County. In the polygon, a depth was given for each grid raster followed by calculat ing the specific flooded area for each parcel of the county The DEM model that HAZUS MH provided for this stage was roughly at a cell size of 30 meter s In order to get more accurate result, the raster would need to be conver ted to a 5 meter cell size for further analysis Figure 3 8 wa s the flowchart for the met hodology of the case study of Volusia County, Florida. The m ain steps taken to quantify the loss of the SS hazard by land use wer e explained in the list below. Step One Clip Volusia 2010 parcel data by floodplain boundary fro m the Base Scenario Add a F ield in the attribute table, for flooded area Export Data as the primary parcel data and get a second copy. One is for convert feature to raster in step two; the other is for projection in step three. The order of step 2 and step 3 can be switch ed Ste p Two Bring up a blank ArcMap map document with the DEM raster data, which was an inundation depth based on 100 yr single return period flooding chance for Volusia County. It could be directly used for Alternative Scenario I. Whenever doing the raster

PAGE 35

35 anal ysis, Environm ent Setting is very important. Here the 5 cell size DEM raster is applied for both Extent in the General Setting and the Cell Size in the Raster Analysis. Figure 3 8 Flowcharts for step s of GIS m ethodology Spatial Analysis for Regional DEM raster data with Spatial Analysis Tools Times to change the cell size from roughly 30 to 5 Single Output Map Algebra with the equation, INT ( rpd100_c_5 12 ), to get the DEM model by inch.

PAGE 36

36 Extract data from the primary parcel data for water body and data with no value, and use the rest for further analysis. Convert the newer parcel data with Polygon to Raster Add a field for user defined ID, which in field calculator expression is FID + 1 with the type of long integer. Zonal Stati stics By Table for the raster attribute data Step Three Project the primary parcel data copy from step one. Calculate geometry for the field of flooded area in the attribute table by US a cres Join the output zonal stats data with parcel data by value and user defined ID. Step Four Summar ize tables, statistic analysis and further analysis Detailed analysis and description is shown in the Chapter 4. Alternative Scenario II The Alternative Scenario II is a storm surge simulated with 1.5m sea level rise scena rio. Sea level rise is one of the natur al hazards that will cause tremendous loss of land along the coastline The phenomenon of global sea level rise is caused by many factors, such as global warming upper ocean thermal expansion etc. Although the resea rch results by different researchers and scientists may vary, sea level rise is an unquestionable fact over the past century. Since the late 19th century, sea level has risen more than 10 c entimeters (IPCC, 2007) Sea level rise will have severe impact s The previous two s cenarios are ideally projected without the variable of sea level rise. In the third scenario 1.5 meter ( approximately 4.9 feet) sea level rise is taken into consideration. One effective way to achieve the goal of bringing the SS analysis on top of the pro jected sea level is to subtract a certain height or depth from the DEM model

PAGE 37

37 produced by HAZUS MH, which was used in the former two scenarios. The methodology to maintain the loss estimation is the same as the one used in Alternative Scenario I

PAGE 38

38 CHAPTER 4 FINDINGS AND RESULTS Base Scenario As shown in table of building exposure by occupancy in A ppendix A the global summary report produced by HAZUS MH indicated that: there are about 2 million buildings affected by the hazard with a loss of value in 2006 do llars of 34 thousand million. T he majority of the damaged buildings wer e residential ones accounting for 76.3 % of the total loss while commercial building damage was one fifth of that for the residential ones. A comparison building loss by different land use type s in A ppendix A shows that the content of the building loss es were weight ed differently by land use type. For residential uses the building losses were weighted more than the loss for content. Conversely for all other uses the building losses were weighted lower than the content loss. Alternative Scenario s Both the alternative scenarios we re applied with Year 2010 tax parcel data. The latest inventory data for HAZUS MH is for Year 2000.Cencus data. Census 2 010 data has been recently released. Once it has been updated for HAZUS MH, the process for Base Sce nario could be run again and may produce more proximal results. The parcel data is categorized by the description accomplished with a certain land use code according to the code from the Florida Dep artment of Revenue. For instance, land use codes from number 000 to 009 are residential, 010 to 039 are commercial, 040 to 049 are i ndustrial, 50 to 69 are agricultur al 070 to 079 are institutional, and 080 to 089 are governmental ( FDOR, 2011).

PAGE 39

39 Define Bui lding Loss According to the depth damage function by Kiefer and Willett (Willett, 1996) t he equation could be written in two expr essions. The first one is without basement. The second one is with a basement. % structure damage = % structure damage = Table 4 1 Parameters for depth damage equit ation for estimating building losses Depth of Inundated (ft) Structure damage (%) Without basement With basement [0, 1] 4.6 11 [1, 4] 20 25 [4, 8] 39 42 [8, 12] 53 55 [12, 20] 63 64 In both of the alternative scenarios, structures assumed with out basement ha d lower loss estimation. The assumptions were made according to the main structure situations in Florida coastal areas where there were seldom basement for building constructions. Comparison: Alternative Scenario I Base Scenario A s shown in T able 4 2, a total of 72403.9 acres of land was analyzed in Alternative S cenario I. A proportion of 10% Volusia was under water by different depth s A total loss of direct building damage for residential uses was around $2.76 billion dollars. The loss estim ation was a little lower than the result by HAZUS MH with Census 2000 data which was $3.28 billion dollars (Figure 4 2) However, the commercial use building loss by Year 2010 parcel data was about $ 3.1 billion dollars which account ed for half of the buil ding loss of $5 95 billion dollars by HAZUS. Similarly, a loss of $98 million dollars for industry occurred in Alternative Scenario I compared with a loss of $171 million dollars

PAGE 40

40 for industry structure damage loss from HAZUS MH default data inventory. A t otal loss for Alternative Scenario I of $2 .76 billion dollars occurred compared to the total loss of $3 99 billion dollars from the Base Scenario (Figure 4 2) The lower loss in the Alternative Scenario I may due to the changes during the 10 y ear s time fra me or a n error when taking different depth damage function into the calculation. Table 4 2 Total building damage due to 100 yr SS by year 2010 parcel Volusia Florida (thousand dollars) Major use Sum_ B lg s Inundated area Dollar loss Percent Agriculture 186 4733.4 $8,595 0.24% Commercial 5771 5199.2 $309,982 8.65% Entertainment 824 2128.7 $61,471 1.72% Government 1681 14266.1 $194,549 5.43% Industry 1839 1696.9 $98,305 2.74% Institutional 1052 1558.4 $128,200 3.58% Miscellaneous 357 1315.0 $15,705 0.44% Not zoned agriculture 99 2566.5 $1,949 0.05% Residential 98348 38939.8 $2,763,893 77.15% T otal 110157 72403.9 $3,582,654 100.00% As a result a lower than ave rage estimation of loss was obtained in the analysis for the 100 yr storm surge with Ye ar 2010 p arcel data for Volusia County, except for the loss estimation for residential building loss. Based on the same consideration the result from Alternative Scenario II, which took sea level rise risk into consideration, could also be a lower estimat ion as well. Comparison: Alternative Scenario I Alternative Scenario II With 1.5m sea level rise (Table 4 3), an additional area of 229,551 acres w ould be under water and additional $1 .52 billion dollars of real property Under a conservative estimation a 1.5m sea level rise could cause 30% more of Volusia County to be under water. Of the inundated land 4% would be residential uses and 24% would be agricultural uses The additional 4% loss of residential land would account for more than

PAGE 41

41 15% of all resi dential area in Volusia County creating a short term housing crisis and a need for permanent housing relocation in the long term Table 4 3 Total B uilding damage due to 100 yr SS and 1.5m SLR by 2010 Parcel, Volusia Florida ( thousand dollars) Major use Sum_ B lg s Inundated area Dollar loss Percent Agriculture 435 184619.5 $27,679 0.50% Commercial 6667 6748.1 $442,565 7.988% Entertainment 881 3013.8 $82,808 1.49% Government 2126 23839.3 $333,271 6.02% Industry 2012 2271.8 $134,161 2.42% Institutional 1351 2647.2 $192,635 3.48% Miscellaneous 388 2745.4 $22,163 0.40% Not zoned agriculture 230 9294.4 $6,958 0.13% Residential 125306 66775.4 $4,298,139 77.58% T otal 139396 301954.9 $5,097,915 100.00% A set of data points for main land use types were s elected from Table 4 8 to Table 4 1 1 at the end of this chapter. The summarizations of the data are represented in Table 4 4 to Table4 7 An analysis for the relation ship between the losses of building value, the land use type and inundation depth was deve loped. Figure 4 1 shows the inundated area of Volusia County would be by land use type if the 0.01 chance of flooding ha d happened. Figure 4 2 show s the inundated area of Volusia County would be by land use type if both the coastal flood hazard and the sea level rise threat were considered. With the consideration of a 1.5m SLR, much more residential and agriculture land w ould be under water. With the SLR, the county would lose most of its land, and the coastline w ould significantly move inland. Comparing th e inundation maps in Figure 4 3 and Figure 4 4 there is only a n area of central land w ould remai n above the water including a certain area of existing water bod ies such as rivers, lakes, and wetlands The more direct loss from sea level rise could be vis ualized through the comparison.

PAGE 42

42 Figure 4 1 Land use map for Alternative Scenario I of SS hazard, Volusia, Florida

PAGE 43

43 Figure 4 2 Land Use Map for Alternative Scenario I I of SS and a 1.5M SLR hazard Volusia Florida

PAGE 44

44 Figure 4 3 Inundation depth map fo r Alternative Scenario I of SS hazard, Volusia, Florida

PAGE 45

45 Figure 4 4 Inundation depth map for Alternative Scenario II of 100 yr SS and a 1.5m SLR hazard Volusia, Florida

PAGE 46

46 Figure 4 5 and Figure 4 6 show the pie charts for t otal percentage losses with and without sea level rise. The percentage loss of each land use type change d very little after taking sea level rise into consideration Th is indicate d that a 1.5m sea level rise proportionally induced additional loss for each land use type while the differe nce w ould only be the total loss from the hazards. It was apparent that more damage was induced with sea level rise Figure 4 5 Pie Charts for total percentage losses of building damage by 100 y r SS, Volusia, Florida Figure 4 6 Pie Charts for total percentage losses of building damage by 100 yr SS and 1.5m SLR, Volusia, Florida

PAGE 47

47 Altern ative s cenario I: 100 yr storm s urge Table 4 4 Original table by depth, loss and land use type for 100 yr storm surge (thousand dollars) Depth Residential Commercial In dustry Agriculture Government Entertainment 0.5 $62,210 $5,746 $1,237 $886 $12,231 $1,364 2.5 $421,731 $58,699 $22,834 $6,625 $69,057 $5,291 6 $2,134,298 $248,646 $67,800 $7,705 $156,700 $57,986 10 $2,763,893 $309,982 $98,305 $8,595 $194,549 $61,471 T he loss value as a function of inundation depth was presented in Figure 4 7 The loss of r esidential building exceeded that of the other building types at different inundation depth T he second biggest loss c ame from commercial building s which only accou nt ed for one tenth of that of the residential building s Figure 4 7 Building Loss by different land use type in the function of inundation depth for 100yr storm s urge In order to better illustrate the dependence of loss value on inundation depth for di fferent type of buildings the loss at different inundation depth s was normalized to the maximum loss value of each particular category The normalized losses are plotted in

PAGE 48

48 Figure 4 8 The steeper increase of loss as a function of inundation depth indica tes th at more particular type s of building were more susceptible to flo od hazard Table 4 5 Normalized table by depth, los s and land use type for 100 yr storm s urge Depth Residential Commercial Industry Agriculture Government Entertainment 0.5 2.3% 1.9% 1.3% 10.3% 6.3% 2.2% 2.5 15.3% 18.9% 23.2% 77.1% 35.5% 8.6% 6 77.2% 80.2% 69.0% 89.6% 80.5% 94.3% 10 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% Figure 4 8 Building Loss Normalized by different land use type in the function of inundation depth for 100yr storm s urge In Figure 4 8 the residential buildings show ed a steady increas e in losses with an increase in inundation depth indicating that the se buildings constantly received the same level of damage at various depths Th is scenario is similar for buildin gs on commercial, industrial and governmental areas. The loss for entertainment areas show s substantial increase as the depth goes beyond 2 feet. This suggest ed most of buildings in entertainment areas might locate to high er ground compared to othe r buildings. Only when the depth level reaches as high as 2 feet, does the influence on entertainment

PAGE 49

49 areas become apparent The loss for agricultural area exhibits different ly More than 80% of the loss occur red when the depth level increase d from 0 to 3f t, indicat ing that most of the agricultural areas were distribute d at lower ground levels Alternative s cenario I I: 100 yr storm s urge and a 1.5m s ea l evel r ise The same process was done for the Alternative Scenario II. Table 4 6 Normalized table by depth loss and land use type for 100 yr storm surge and a 1.5m sea level rise (thousand dollars) Depth Residential Commercial Industry Agriculture Government Entertainment 0.5 $29,293 $3,325 $665 $834 $4,770 $117 2.5 $515,312 $71,698 $16,516 $6,077 $89,953 $ 6,070 6 $1,812,096 $161,239 $49,365 $22,518 $186,715 $54,989 10 $4,298,119 $442,468 $134,161 $27,679 $333,271 $82,808 Figure 4 9 Building Loss by different land use type in the function of inundation depth for 100yr Storm Surg e and a 1.5 m s ea l evel r ise Figure 4 9 shows the loss of different buildings with the consideration of a storm surge plus a 1.5m sea level rise. More loss occurs when 1.5m sea level rise is considered. The loss from residential buildings is almost twice that of the scenario

PAGE 50

50 with out sea level rise. Different levels of increased loss are observed in other type of buildings. Table 4 7 Normalized table by depth, loss and land use type f or 100 yr storm surge and 1.5m sea level r ise Depth Residential Commercial Industry Agriculture G overnment Entertainment 0.5 0.7% 0.8% 0.5% 3.0% 1.4% 0.1% 2.5 12.0% 16.2% 12.3% 22.0% 27.0% 7.3% 6 42.2% 36.4% 36.8% 81.4% 56.0% 66.4% 10 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% Figure 4 10 Building Loss Normalized by different land use type in the function of inundation depth for 100yr storm surge and a 1.5 m sea level rise As shown in Figure 4 10, the dependence of loss on inundation depth shows less variation for different types of buildings compared to those of the scenario without sea level r ise. All types of building show a relatively linear increase of loss with depth level. Deviation from such linearity is only observed in agricultural and entertainment buildings. This may attributed to the non uniform distribution of the particular buildin gs along the altitude. All these indicate the loss pattern will change with the sea level rise and additional care should be taken.

PAGE 51

51 Table 4 8 Controlle d building damage bet ween WS/WO SLR by 2010 p arcel, i nundation between 0 1ft (thousand dollars) Inun dated between 0 to 1 feet W/o sea level rise 1.5 m (4.9 feet) sea level rise Major use Sum_Blgs Inundated area Dollar loss Percent Sum_Blgs Inundated area Dollar loss Percent Agriculture 79 1424.9 $886 0.99% 109 17680.7 $834 1.96% Commercial 489 446.8 $5,746 6.40% 414 130.3 $3,325 7.81% Entertainment 62 308.1 $1,364 1.52% 27 55.6 $117 0.28% Government 237 620.9 $12,231 13.62% 276 965.9 $4,770 11.21% Industry 86 91.5 $1,237 1.38% 89 44.5 $665 1.56% Institutional 224 241.0 $4,764 5.30% 220 367.8 $2,8 63 6.73% Miscellaneous 50 114.1 $1,031 1.15% 8 8.7 $466 1.09% Not zoned agriculture 40 226.6 $354 0.39% 49 571.0 $228 0.54% Residential 11511 4411.1 $62,210 69.26% 8707 4856.9 $29,293 68.82% Total 12778 7885.0 $89,828 100.00% 9899 24681.3 $42,564 100.0 0%

PAGE 52

52 Table 4 9 Controlled building damage between WS/W O SLR by 2010 p arcel, i nundation between 1 4 ft (thousand dollars) Inundated between 1 to 4 feet W/o sea level rise 1.5 m (4.9 feet) sea level rise Major use Sum_ B lg s Inundated area Dollar loss P ercent Sum_ B lg s Inundated area Dollar loss Percent Agriculture 78 3054.5 $5,739 1.09% 137 51889.7 $5,243 0.74% Commercial 586 1243.9 $52,952 10.09% 1072 1431.5 $68,373 9.67% Entertainment 111 948.1 $3,926 0.75% 100 1059.2 $5,953 0.84% Government 392 46 06.6 $56,826 10.83% 468 4201.6 $85,183 12.05% Industry 333 563.7 $21,596 4.12% 221 687.0 $15,851 2.24% Institutional 169 416.6 $14,222 2.71% 261 799.8 $25,925 3.67% Miscellaneous 230 968.0 $8,951 1.71% 230 652.0 $11,966, 1.69% Not zoned agriculture 30 1201.3 $965 0.18% 88 3638.0 $2,530 0.36% Residential 16972 10602.1 $359,520 68.52% 26083 17243.6 $486,018 68.74% Total 18901 23604.7 $524,701 100.00% 28660 81602.4 $707,047 100.00%

PAGE 53

53 Table 4 1 0 Controlled building damage between WS/ WO SLR by 2010 p arcel i nundation between 4 8ft (thousand dollars) Inundated between 4 to 8 feet W/o sea level rise 1.5 m (4.9 feet) sea level rise Major use Sum_blg Inundated area Dollar loss Percent Sum_blg Inundated area Dollar loss Percent Agriculture 19 193.8 $1,079 0.05% 151 90533.9 $16,441 1.01% Commercial 3528 2614.3 $189,946 8.75% 1032 1738.5 $89,540 5.50% Entertainment 561 608.2 $52,695 2.43% 285 1091.5 $48,918 3.00% Government 738 7584.4 $87,642 4.04% 405 5598.6 $96,761 5.94% Industry 912 703.8 $44,966 2.07 % 398 559.2 $32,848 2.02% Institutional 478 632.8 $79,849 3.68% 271 680.3 $39,842 2.45% Miscellaneous 46 139.9 $2,499 0.12% 88 1750.5 $4,052 0.25% Not zoned agriculture 25 942.5 $449 0.02% 60 3758.6 $3,258 0.20% Residential 56448 17970.6 $1,712,567 78 .86% 31114 21302.9 $1,296,784 79.63% Total 62755 31390.3 $2,171,697 100.00% 33804 127013.9 $1,628,448 100.00%

PAGE 54

54 Table 4 1 1 C ontrolled building damage between WS/WO SLR by 2010 parcel, inundation between 8 12 ft (thousand dollars) Inundated between 8 to 12 feet W/o sea level rise 1.5 m (4.9 feet) sea level rise Major use Sum_Blgs Inundated area Dollar loss Percent Sum_ B lg Inundated area Dollar loss Percent Agriculture 10 60.2 $890 0.11% 38 24515.2 $5,160 0.16% Commercial 1168 894.2 $61,33 6 7.70% 414 5 3443.5 $281,228 8.89% Entertainment 90 264.3 $3,484 0.44% 469 807.6 $27,818 0.88% Government 314 1454.2 $37,848 4.75% 977 13073.2 $146,556 4.63% Industry 508 337.9 $30,504 3.83% 1304 981.1 $84,795 2.68% Institutional 181 268.0 $29,363 3.69% 599 799.3 $124,003 3.92% Miscellaneous 31 93.0 $3,223 0.40% 62 334.2 $5,678 0.18% Not zoned agriculture 4 196.2 $180 0.02% 33 1326.8 $941 0.03% Residential 13417 5956.0 $629,594 79.05% 59401 23369.6 $2,486,022 78.62% Total 15723 9523.8 $796,427 100.00% 67028 68 650.4 $3,162,207 100.00%

PAGE 55

55 Table 4 1 2 Controlled building damage bet ween WS/WO SLR by 2010 p arcel, i nundation above 12 ft Inundated above 12 feet W/o sea level rise 1.5 m (4.9 feet) sea level rise Major use Sum _B lg s Inundated area Dollar loss Percent Sum_ B lg s Inundated area Dollar loss Percent Agriculture Commercial 4 4.4 $97,151 Entertainment Government Industry Institutional Miscellaneous Not zoned agriculture Residential 1 2.5 $19,851 Total

PAGE 56

56 CHAPTER 5 DISCUSSION Discussion of Findings and Methods To calcul ate the losses due to flood is a complicate d and comprehensive work. Many factors coul d add up to the sum of the loss. Both direct loss and indirect loss should be considered Direct loss includes the physical damages of the building, the direct economic loss, the c rop loss, shelter for people I ndirect loss includes the upcoming wildfire, removal of debris peoples relocation or the areas redevelopment (Zhang, et al., 2011) There are particular damage functions for different categories suffered fr om flooding. For example, the loss of building content is usually calculated by cor relating the characteristics of the buildings by weight to a certain percentage of the building value. For the Volusia case study, further in depth research should be carrie d out to define those certain parameters. ( Davis 1992) Other than that, a more accurate conclusion could be drawn. However, debates come up in some specific field T he damage function for agricultur al land need s to be discussed because some research shows that after certain intens e flood s might even bring benefits to the agriculture land, as the soil become s more fertile after the flood However, e fficient evaluation of the criteria is of critical importance in the pro cess of comparing the results of projected scenarios. A good evaluation should be comprehensive enough to clarify the results of the associated objectives as well as be measurable for a more convincible quantitative an alysis At last it should be representative, which means it could fully cover certain aspect s of the situation and

PAGE 57

57 would not be confusing to cause double counting either for further analysis for conclusion drawing out, or for decision making. (Rashed & Weeks, 2003) Other than d epth, some other primary factors such as velocity of water during the flooding period and h ow long it takes for water to reced e the after the flooding period are also contributing to flood losses. (Bullock, et al. 2008) Some other type of hazards associated with flooding could also contribute to flood losses, suggesting, more damage functions needs to be figure d out through future research. On the other hand, the data used in this research is the best available data in reach. Nevertheless the method in data inventory could be improved. HAZUS MH level 2 provide a platform which is Comprehensive Data Management Syste m (CDMS) tool. By exploring this, more updated date from the newest census or curves on site could be processed in the software, such as the population, numbers and types of the buildings, and other related parameters. Future Research Opportunities R. Klei n and R. Nicholls proposed three level of assessment to the vulnerability of coastal area by the limited available data P lanning assessment (PA) is considered t o be the in depth criticism with the suitability analysis. The other two level s in order are sc reening assessment (SA) to get a fa c ade view to the vulnerability and then v ulnerability a ssessment (VA) to have a comprehensive consideration to effects from various aspect might lead to vulnerability. (Nicholls, 1999) In that case, further study on suitability and sustainability analysis in planning scope and appropriate implementation might be formed base on this. Since this type of research could visualize the future possibl e hazards, with more specific and accurate input, the relative scenarios might be created and analyzed to help planners work with emergency managers to develop and

PAGE 58

58 implement disaster plans and mitigation plans and to assist with disaster response activitie s On the other hand, planning strategies development may also take the visualized results into consideration to make mitigation plans and evacuation plans for short term use, and land use adaptation plans and population reallocation plans for long term u se.

PAGE 59

59 CHAPTER 6 CONCLUSION In this study, t he Base Scenario is ideal ly static with variables including population growth land use change, socio economic status, and changes in the natural environment are not taken into account This scenario however, i s necessary to compare future possibilities The Alternative Scenario I use s Year 2010 tax parcel data and a Volusia County DEM raster to estimate building loss by land use types with Kiefer and Willett s depth damage function. The estimation was with an acceptable error and lower than the loss in the Base Scenario. The Alternative Scenario II is based on Alternative Scenario I by incorporating a modified Volusia County DEM raster, which was subtracted by 1.5m (4.9 feet ). This approach intends to simu late a situation with a 1.5m sea level rise. The loss was dramatically increased by this which indicated that sea level rise c an hardly be ignored for an efficient land use planning. Therefore it is important to create an appropriate model and fully eva luate the results in order to determine whether the data is reasonable and ready to be use d for decision making. The decision maker should also carefully interpret the results and provide their own inputs when it is necessary (Darwin & Tol, 2001 ) In addition, it would be helpful to have comparison s between the real events that tak e place and historical, documented losses as well as the existing potential losses to examine the validity of the model Considering the factors that can impact the st udy region, the results can be re run and documented to support mitigation strategies. (Davis, 1985) At this stage one can identify the asset s that are subject to the greatest potential damage (FEMA 2004).

PAGE 60

60 Not only the direct economic losses, but also the indirect loss of the agricultur e land products output industrial products output and damage of the infrastructure are expected to cause mor e severe economic losses due to flood ing by sea level rise and s torm s urge (McLeod, et al., 2010) This also greatly increas es the possibility of bankruptcy of various entities involved due to limit ed coverage of FEMA s mitigation plan and insurance companies Moreover, the extra expense on post disaster resilience will increase the financial burden of local and federal governm ent s which will lead to potential budget cut s in education, health care and other social benefits. The government should not only keep the above fact in mind but also that it is im portant to remind individuals of these risks so that they are willing to sp end more on flood insurance. M any people do not pay attention to the threat of such infrequent risk to their properties. If people could understand that the risks exist, they will be more cooperative and supportive toward the implementation of revised futu re land use and/or evacuation plans in certain areas. However, the extra expense o f these plans has to be afforded by someone which needs to be further discussed Human caused environmental deterioration caused by flooding has been we ll documented. (Cushman, et al. 1991) On the contrary wetlands, swamps, mangroves are ecological ly p ositive with water drainage capacity and they are important in terms of flood prevention. Since the se risks of nature disaster s are inevitable, we should prepare to face the challenges by keep ing up the related systems in pace with that of climate change. The HAZUS MH model should be employed to a greater extent by urban and regional planners. With the application of the model, the long term impacts of storm

PAGE 61

61 surge and sea level rise on infrastructure, property parcels, a nd other public and private resources may be visualized. This research eschews the typical science or engineering schemes to help or prevent inevitable hazard s and to offer visualized scenarios to help relat ed organizations to make more serious decisions to reduce the hazards damage. According to the results of the hypothesis of the research more rational and appropriate coastal county planning implementation should be seriously considered in the future with regard to aspects such as conditional developme nt s caused by climate change, in term s of sea level rise This is likely to be a reasonable approach to allocating limited resources. From a societal perspective, all qualifying proposals are worth pursuing This type of analysis should help politicians to begin to seriously think about whether development within coastal areas is appropriate and what might be the liability associated with those decision s for Florida.

PAGE 62

62 APPENDIX A VOLUSIA 100 YR COASTAL FLOOD EVENT SUMMARY REPORT

PAGE 63

63

PAGE 64

64

PAGE 65

65

PAGE 66

66

PAGE 67

67

PAGE 68

68

PAGE 69

69

PAGE 70

70

PAGE 71

71

PAGE 72

72

PAGE 73

73 APPENDIX B V OLUSIA 100 YR COASTAL FLOOD EVENT QUICK ASSESSMENT REPORT

PAGE 74

74 LIST OF REFERENCES Bullock, J. A., Haddow, G. D., & Haddow, K. S. (2008). Global Warming, Natural Hazards, and Emergency Management. Boca Raton: CRC Press Cushman, R. M., Gorn itz, V. G., & White, T. W. (1991). In Oak Ridge National Laboratory., United States. Dept. of Defense., United States. Dept. of Energy. and United States. Dept. of Energy. Office of Scientific and Technical Information. (Eds.), Vulnerability of the US to f uture sea level rise [electronic resource]. Washington, D.C. : Oak Ridge, Tenn: United States. Dept. of Defense ; distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy. Online at: http://www.osti.gov/bridge/servlets/purl/5875484 vJgAJI/ Darwin, R. F., & Tol, R. S. J. (2001). Estimates of the Economic Effects of Sea Level Rise Environmental and Resource Economics, 19 (2), 113 129. Davis, S. A., Skaggs, L. L., & U.S. Army Engineer Institute for Water Resources. (1992). Catalog of residential depth damage functions used by the Army Corps of Engineers in flood damage estimations. Ft. Belvoir, Va: U.S. Army Corps of Engineers, Water Resources Support Center Institute for Water Resources. Davis, S. A., & U.S. Army Engineer Institute for Water Resources. (1985). Business depth damage analysis procedures Ft. Belvoir, Va: US Army Corps of Engineers, Engineer Institute for Water Resources. FDOR. (2011). 2011 pr oduction guide and data record layout for the comma delimited file format Online at: f tp://sdrftp03.dor.state.fl.us/Tax%20Roll%20Data%20Files/About%202011%20NA L SDF TPP%20Files/2011%20production%20guide%20and%20data%20record%20layou t.pdf FEMA. (2011). Flood insurance study: Volusia County, Florida and incorporated areas Washington, D.C.: Federal Emergency Management Agency. FEMA. (2011) Hazus MH MR5 multi hazard loss estimation methodology flood information tool user manual. Online at: http://www.fema.gov/library/viewR ecor d.do?id=4454 Accessed (05.07.11) FEMA. (2011) Hazus MH MR5 multi hazard loss estimation methodology flood mod el technical manual. Online at : http://www.fema.go v/library/viewRecord.do?id=445 4 Accessed (05.07.11) FEMA. (2011) Hazus MH MR5 multi hazard loss estimation methodology flood model user manual. Online at: http://www.fema.gov/library/viewRecord.do? id=4454 Accessed (05 .07.11)

PAGE 75

75 IPCC. (2007). Climate change 2007: impacts, adaption and vulnerability. O nline at: http://www. ipcc.ch/publications_and_data/publications_ipcc_fourth_assessment_r eport_wg2_report_impacts_adaptation_and_vulnerability.htm Accessed (08.08.11) Matisziw, T., & Grubesic, T. H. (2011). Geographic perspectives on vulnerability analysis. GeoJournal Online at: http://www.springerlink.com/content/y67288739t348w47/fulltext.pdf Accessed (09.10.11) McLeod, E., Hinkel, J., Vafeidis, A., Nicholls, R., Harvey, N., & Salm, R. (2010). Sea level rise vulnerability in the countries of the Coral Triangle Sustainability Science 5 (2), pp 207 222. Murley, J. F. (2004). Assessment of Redefining Florida's Coastal High Hazard Area Online at: http://docs.cdsi.fau.edu/cues/CHHAFINALREPORT MAY212008.pdf Accessed (05.07.11) Nicholls, R. J (1999). Assessment of Coastal Vulnerability to Climate Change Ambio 28 (2), pp 182 187. O liver, C. E. (2010). Catastrophic disaster p lanning and response Boca Raton: CRC Press Puszkin, C. A., Hernandez, D., & Murley, J. (2006). Land use planning and its potential to reduce hazard vulnerability: Current practices and future possibilities Marine Technology Society Journal, 40 (4), pp 7 1 5. Rashed, T., & Weeks, J. (2003). Assessing vulnerability to earthquake hazards through spatial multicriteria analysis of urban areas. International Journal of Geographical Information Science, 17 (6), pp 547 576. Simpson, D. M. (1998). Risk and disaster: A rguments for a community based planning approach Berkley Planning Journal, 7 Titus, J. G., & Richman, C. (2001). Maps of lands vulnerable to sea level rise: modeled elevations along the US Atlantic and Gulf coasts Climate research, 18 (3), pp 205 228. Viv ien, G. (1991). Global coastal hazards from future sea level rise. Global and Planetary Change, 3 (4), pp379 398. Willett, J. C. (1996). Analysis of Non Residential Content Value and Depth Damage Data for Flood Damage Reduction Studies Online at: http://www.iwr.usace.army.mil/docs/iwrreports/96 R 12.pdf Accessed (09.10.11) Zhang, K ., Ross M & Bergh C. (2011). Assessment of sea level rise impacts on human population and real pro perty in the Florida Keys Climatic Change, 107 pp 129 146.

PAGE 76

76 BIOGRAPHICAL SKETCH Yuyang Zou was born in 1984 in Hubei, China. She has a degree of Bachelor of Architecture from Huazhong University of Science and Technology. She is pursuing her degree of M aster of Arts in Urban and Regional Planning at University of Florida. She has worked as a research assistant for Dr. Paul Zwick since 2009. Her masters studies are focused on GIS based analysis for nature hazards and land use suitability models. She has also been a research assistant at in the Shimberg center for Housing Studies since May 2011. Her research at the Shimberg Center involves the development of the Affordability Housing Suitability Model. She will continue the research her after graduation.