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Small drainage basins and the probable maximum flood

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Title:
Small drainage basins and the probable maximum flood a flood inundation study of an anticipated extreme storm event in West Central Florida
Physical Description:
Book
Language:
English
Creator:
Ranalli, Philip Anthony
Publisher:
University of South Florida
Place of Publication:
Tampa, Fla.
Publication Date:

Subjects

Subjects / Keywords:
PMF
Karst
physiographic
severe
hurricane
Dissertations, Academic -- Geography -- Masters -- USF   ( lcsh )
Genre:
government publication (state, provincial, terriorial, dependent)   ( marcgt )
bibliography   ( marcgt )
theses   ( marcgt )
non-fiction   ( marcgt )

Notes

Summary:
ABSTRACT: A major tropical storm will strike in the area of West Central Florida. In anticipation of this storm, this study seeks to predict the specific areas within the Baker Canal drainage basin that will be inundated as a result of this expected event. There are few references concerning extreme flooding in small drainage basins within existing literature. For the purposes of this study this event was considered to be a Probable Maximum Flood (PMF) as defined by Crippen and Bue (1977). The Hydrologic Engineering Centers' Geographic River Analysis System was used to develop water surface elevations and flow rates. Maps depicting this potential flooding at various flood stages were produced using the Environmental Survey Research Institute's geographic Information mapping program ArcView3.3. This investigation produced estimates of the surface area of a Probable Maximum Flood and the estimated flood inundated 23.7% of the study area. The estimated extent of Probable Maximum Flood indicates that the flood will affect one thousand and seventy six (1,076) homes and other structures. The study found that eight hundred and sixty three (863) acres or 27% of the land within the PMF flood zone is listed for future development by the County Planning Commission. When this projected development area is added to existing developed land area a total of 85% of all developed land within the estimated flood area will be submerged and subject to damage. An extreme flood study on a small drainage basin prior to the event can be a viable tool for mitigation planning if it is recognized that there are variables that can produce a relatively large range of error. The potential for this type of study is in its' comparison with an actual event affecting the same area. If the predicted study and the real event study agree within reasonable limits then, maximum flood investigations on small basins could be considered a useful tool in hazard reduction.
Thesis:
Thesis (M.A.)--University of South Florida, 2004.
Bibliography:
Includes bibliographical references.
System Details:
System requirements: World Wide Web browser and PDF reader.
System Details:
Mode of access: World Wide Web.
Statement of Responsibility:
by Philip Anthony Ranalli.
General Note:
Title from PDF of title page.
General Note:
Document formatted into pages; contains 133 pages.

Record Information

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University of South Florida Library
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University of South Florida
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All applicable rights reserved by the source institution and holding location.
Resource Identifier:
aleph - 001474322
oclc - 56137741
notis - AJR7191
usfldc doi - E14-SFE0000367
usfldc handle - e14.367
System ID:
SFS0025061:00001


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ABSTRACT: A major tropical storm will strike in the area of West Central Florida. In anticipation of this storm, this study seeks to predict the specific areas within the Baker Canal drainage basin that will be inundated as a result of this expected event. There are few references concerning extreme flooding in small drainage basins within existing literature. For the purposes of this study this event was considered to be a Probable Maximum Flood (PMF) as defined by Crippen and Bue (1977). The Hydrologic Engineering Centers' Geographic River Analysis System was used to develop water surface elevations and flow rates. Maps depicting this potential flooding at various flood stages were produced using the Environmental Survey Research Institute's geographic Information mapping program ArcView3.3. This investigation produced estimates of the surface area of a Probable Maximum Flood and the estimated flood inundated 23.7% of the study area. The estimated extent of Probable Maximum Flood indicates that the flood will affect one thousand and seventy six (1,076) homes and other structures. The study found that eight hundred and sixty three (863) acres or 27% of the land within the PMF flood zone is listed for future development by the County Planning Commission. When this projected development area is added to existing developed land area a total of 85% of all developed land within the estimated flood area will be submerged and subject to damage. An extreme flood study on a small drainage basin prior to the event can be a viable tool for mitigation planning if it is recognized that there are variables that can produce a relatively large range of error. The potential for this type of study is in its' comparison with an actual event affecting the same area. If the predicted study and the real event study agree within reasonable limits then, maximum flood investigations on small basins could be considered a useful tool in hazard reduction.
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PAGE 1

Small Drainage Basins and the Probable Maximum Flood: A Flood Inundation Study of an Anticipated Extreme Storm Event in West Central Florida by Philip Anthony Ranalli A thesis submitted in partial fulfillment of the requirements for the degree of Master of Arts Department of Geography College of Arts and Science University of South Florida Major Professor: Graham A. Tobin, Ph.D. Paul Zandbergen, Ph.D. Philip Reeder, Ph.D. Date of Approval: June 25, 2004 Keywords: PMF, Karst, Physiographic, Severe, Hurricane Copyright 2004, Philip A. Ranalli

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ACKNOWLEDGMENTS I express my thanks to my advisory committee for their willingness to do the considerable work involved in directing my ef forts in this endeavor. Special thanks are due Dr. Graham A. Tobin for his interest ing and well designed classes in Hydrology, Hazards, and Water Resources. Dr. Tobins willingness to be available for consultation and his support and encouragement were even more important. Dr. Paul Zandbergens class in Advanced Geographic Information Sy stems was invaluable, as were his guidance and suggestions. Dr. Philip Reeders support a nd assistance in providi ng material directly related to this type of st udy is greatly appreciated. Special thanks are due to my wife Ba rbara for her patience and encouragement. Many others have assisted, some in ways of which they are not aware. Lastly I thank God for granting the time and opportunity for this effort.

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TABLE OF CONTENTS List of Tables iii List of Figures iiii List of Pictures vii Abstract viii Chapter One Introduction 1 Goals of Study 3 Chapter Two Literature Review 7 About the Area 17 Theory 23 Geographic Information Systems 25 Research Questions 27 Chapter Three Study Area 28 Selfer Drainage Basin 31 Specific Area 34 Study Area Lakes 36 Land-Use 37 Future Land-Use 39 Zoning 40 Study Area Characteristics 41 Temperature 41 i

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Evapotranspiration 41 Geology 41 Surficial Aquifer 44 Baker Canal Pictures 46 Chapter Four Methodology 53 Data Acquisition 54 General Metadata 60 Possible Problems 61 Computer Programs 63 Computation Procedure 65 Operational Procedure 69 Chapter Five Results 73 Input Data for Calculations 73 Discussion 81 Flood Area 86 Example Analysis 92 Chapter Six Conclusion 110 General Procedure 111 Flood Impact 111 Suitability of Methods Used 116 Follow-up Study 118 ii

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LIST OF TABLES Table 1 Norma Lake Levels 34 Table 2 Landuse Baker Canal by Percent 36 Table 3 Zoning by Percent of Area 40 Table 4 Soil Types 42 Table 5 Model Output Table 108 Table 5 Model Output Table continued 109 Table 6 Comparison of Flood Areas 112 Table 7 Flood Area Landuse by Percent 113 iii

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LIST OF FIGURES Figure 1. Leading Cause of Cyclone Deaths 10 Figure 2. Record Maximum Precipitation in U.S. 15 Figure 3. Hurricane Track 1921 19 Figure 4. Physiographic regions of ma ximum flood flows 23 Figure 5. Study Area Location Map Florida 30 Figure 6. Study Area Location Map County 31 Figure 7. Specific Study Area 33 Figure 8. Study Area Lakes 35 Figure 9. Study Area Land Use Map 37 Figure 10. Expected Land Development Map 38 Figure 11. Study Area Zoning 39 Figure 12. Study Area Soils 43 Figure 13. Ground Water Contours 45 Figure 15. Two Ft. Contours 56 Figure 16. Five Ft. Contours 57 Figure 17. Five Ft. Contours over Two Foot Contours 58 Figure 18. Digitized Two Foot Contours 59 iiii

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Figure 19. Rating Curve 62 Figure 20. Maximum 24 hour rainfall 74 Figure 21. National Flood Frequency (NFF) flow data 75 Figure 22. Parameters for NFF Flow Data 76 Figure 23. PreRAS prompt of HECGeoRAS 77 Figure 24. Geometric Data Diagram 78 Figure 25. Steady Flow Input Data 79 Figure 26. Steady Flow Boundary Input 80 Figure 27. HEC 100yr flood over Hillsborough 100yr flood 83 Figure 28. Hillsborough 100yr flood over HEC 100yr flood 84 Figure 29. FEMA Flood Risk Area 85 Figure 30. HEC 100yr flood over HEC 500 yr flood 87 Figure 31. HEC 500yr flood over HEC 100yr flood 88 Figure 32. HEC 100yr flood depth 89 Figure 33. HEC 500yr flood depth 90 Figure 34. Probable Maximum Flood 91 Figure 35. PMF at Muck Pond Rd. 93 Figure 36. PMF South of State Highway 92 94 Figure 37. Enlarged Map of PMF S. Hwy 92 95 Figure 38. PMF North of Wheeler Rd. 96 Figure 39. PMF at Lake Shore Ranch Subdivision 97 Figure 40. PMF at Long Pond and Lake Valrico 98 v

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Figure 41. Enlarged Map of Lake Valrico 99 Figure 42. Cross-section at outfall 100 Figure 43. Cross-section S. of State Rd. 92 101 Figure 44. Cross-section at Lake Weeks 101 Figure 45. Cross-section between Long Pond and Lake Hooker 102 Figure 46. Cross-section at Lake Valrico 102 Figure 47. Cross-section at head-waters of study area 103 Figure 48. Profile Baker Canal at PMF level 104 Figure 49. Profile Tributary 1 105 Figure 50. ChartTop width of PMF 106 Figure 51. ChartVelocity of PMF 107 Figure 52. Land-use within PMF zone 116 vi

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LIST OF PICTURES Picture 1 Baker Canal N. of Muck Pond Rd. 46 Picture 2 Baker Canal S. of Muck Pond Rd. 47 Picture 3 Baker Canal N. of State Rd. 92 48 Picture 4 Baker Canal S. of State Rd. 92 49 Picture 5 Baker Canal under County Rd. 574 50 Picture 6 Lake Valrico Water-front Home 51 Picture 7 Lake Valrico New Construction 52 vii

PAGE 10

SMALL DRAINAGE BASINS AND THE PROBABLE MAXIMUM FLOOD: A FLOOD INUNDATION STUDY OF AN ANTICIPATED EXTREME STORM EVENT IN WEST CENTRAL FLORIDA Philip A. Ranalli ABSTRACT A major tropical storm will strike in the area of West Central Florida. In anticipation of this storm, th is study seeks to predict the sp ecific areas within the Baker Canal drainage basin that will be inundated as a result of this expected event. There are few references concerning extreme flooding in small drainage basins within existing literature. For the purposes of this study this ev ent was considered to be a Probable Maximum Flood (PMF) as defined by Cr ippen and Bue (1977). The Hydrologic Engineering Centers Geographic River Analysis System was used to develop water surface elevations and flow rates. Maps de picting this potential flooding at various flood stages were produced using the Environmenta l Survey Research Institutes geographic Information mapping program ArcView3.3. This investigation produced estimates of the surface area of a Probable Maximum Flood and the estimated flood inundated 23.7% of the study area. The estimated extent of Probable Maximum Flood indicate s that the flood will affect one thousand and seventy six (1,076) homes and other structures. Th e study found that eight hundred and sixty three (863) acres or 27% of the land within the PMF flood zone is listed for future viii

PAGE 11

development by the County Planning Commi ssion. When this projected development area is added to existing developed land area a total of 85% of all developed land within the estimated flood area will be submerged and subject to damage. An extreme flood study on a small drainage basin prior to the event can be a viable tool for mitigation planning if it is r ecognized that there are variables that can produce a relatively large range of error. The potential for this type of study is in its comparison with an actual even t affecting the same area. If the predicted study and the real event study agree within reasonable li mits then, maximum flood investigations on small basins could be considered a useful tool in hazard reduction. viiii

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1 CHAPTER ONE INTRODUCTION Flood research is usually confined to inve stigations after the fact. The physical event occurs, social changes begin to take place, cultural changes follow or occur simultaneously, and then research into these alterations begins. Research is an attempt to record the history of the ev ent and its affects upon the popula tion. The basic theory is that if history is known and understood the same errors will not be repeated and losses will be minimized or mitigation against damage will be more efficient. Unfortunately such has not been the case. Time after time disasters have occurred, and been studied. The event is then repeated again and again at in tervals of several months to tens of years, and is perhaps studied again and again. The history we have been writing has not been heeded to the extent necessary such that it has lessened the frequency or the severity of disasters over all. Perhaps a different line of inquiry may be more effective. Consider the situation that exists now on the West Coast of Florida. A major tropical stor m is expected, exactly when and where this will occur is not pred ictable. However, worst case scenarios are possible based on population densities, proximi ty to the storm, and storm duration and severity. If sufficiently rigorous studies could be performed, prior to this event, on these areas and these studies could be determined to be practically adequate, planning for evacuation and mitigation could be greatly e nhanced. At the very least public awareness

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2 of the magnitude of forthcoming destruction would be increased and further urbanization in hazardous areas may be lessened. It appears that the general public underestimates or is not aware of the potential extent and duration of inland flooding that would occur in a significant storm event (NOAA 2003a). It is possible that the social and economic impacts on the population are also underestimated. Since the causal factors related to the social and economic impacts of severe inland flooding are not widely disseminated, preventati ve action related to education and mitigation planning cannot be taken in an effective manner. This thesis details the methodology necessa ry to investigate the effect of a Probable Maximum Flood (PMF) event in a small drainage basin in West central Florida. The reason for the study, the overall goals, sp ecific goals, positive and negative aspects of the theories used, the study area, expect ed results, and order of execution will be discussed. The overall goal of the study is to determ ine the extent of potential flooding in a chosen area of West central Florida. This investigation will attempt to incorporate a modified Positivist theory to determine the phys ical extent of an extreme flood event. If a follow up study of the actual storm event co mpares favorably with the present study, perhaps this will encourage additional interest in potential storm events in small drainage basins and foster further comparisons. Si gnificant correlation between studies of potential and actual storm flooding may enable efficient mitigation of extreme flooding. Technology has advanced to a degree such th at it is now possible to model a potential extreme storm event. The study will be evaluate d as to its use as a model for similar small

PAGE 14

3 drainage basins that may be subject to flooding as a result of widespread storm precipitation. GOALS OF THE STUDY This study is methodological investigation that seeks to determine if an extreme flood area can be successfully estimated usi ng an easily and inexpensively acquired flood program. The specific goals of the study are to determine the portion of the land surface of the study area that will be submerged by a Probable Maximum Flood (PMF), and to map this flooded area in ways that will allow an alysis. The specific questions that will be examined are: Is the easily acquired and inexpensive flood program, Hydr aulic Engineering Centers River Analysis System (HEC-RAS), a viab le solution to flood inundation on a small drainage basin? What is the area of the study basin that will be inundated by a Probable Maximum Flood? What are some of the significant effects of a Probable Maximum Flood on the study area? Extensive analysis will not be attempted in this thesis. These short-term goals are preliminary to mu ch longer-term goals that are related to a post flood study of the extreme flood event. Th e pre flood predictions are intended to set the stage, as it were, for a possible post flood study. It would be advantageous to establish conditions as they existed prior to a severe flood rather than attempt to discern these

PAGE 15

4 conditions after they have been altered by action of the floodwaters. It is expected that a pre flood data set would be invalu able in a post flood study situation. The pre flood prediction of the area inundated will be compared to the area actually flooded in an actual event. When the event will occur is not known but the occurrence is assured and a post flood study will most assuredly be in itiated if the event is of considerable magnitude. A long-term goal is to demons trate that predictive small drainage basin studies of extreme floods are a viable al ternative to post flood inve stigations. A successful comparison of pre flood prediction and post flood inundation will be a strong indication that in this case at least and possibly in other cases as well, that predictive flood studies of extreme events are viable in small basins. If the pre flood predictions are deemed practically adequate they can be useful for planning purposes such as recommendations as to how rapid the flooding may develop. For example enhanced zoning regulations of ar eas seen to be partic ularly vulnerable to severe flooding could be enacted. Predicted flooding of a severe nature will be of interest in investigations of risk assessment and economic impact. In a pred icted flood, the multifaceted factors involved in economic estimations of flood damage can be pursued at leis ure and without undue pressure from various relief agencies or flood victims as normally occurs in the aftermath of an actual event. Questions as to lost opportu nity, direct or indirect losses, long or short term losses, offsetting benefits, and tangible or intangible losses coul d be considered and compared and then recorded for further compar ison at the time of th e actual occurrence.

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5 If it can be shown that the physical extent of a disaster can be pre-recognized, and convincingly and accurately mapped, within practical adequacy, a powerful tool will have been developed for the mitigation or prevention of extreme events. First, a region is selected in which a particular hazard is known to be active at some interval such that the population is not eminently aware. Then the real but expected events are modeled and mapped prior to the event. The end result could encourage efficient preemptive mitigation, if nothing else it could beget a heightened awareness by the population, and land-use planne rs, not only to the potential of a disaster but also to their possible interaction with the event. The political implications, of this ed ucation of the populat ion, are not without fallout and pitfalls. An educated public may demand a higher standard of disaster management than is now present. It is also possible that when the event does occur, an educated public may hold political appointee s responsible for inadequate planning. Any of these possible situ ations could result in reluctan ce to support such studies. Nevertheless, the possibilities are prof ound, and it behooves the geographic community to pursue potentially benefici al methods of investigation. Risk assessment is more convoluted than economic impact. However this case of Probable Maximum Flood does eliminate magni tude as a factor of variability. Probability remains extremely low, but flood damage rises rapidly as magnitude increases. Thus economic risk remains high, a nd high risk drives disa ster investigations. The long-term goals are dependent upon th e occurrence of a se vere flood within a reasonable time frame. If an excessive amount of time passes between a pre-flood prediction and post-flood investig ation, much of the pre-flood physical data will be dated,

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6 and the social occupation of the basin will ha ve changed. If the pre-flood study is not done, we will however, have missed a rare opportunity.

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7 CHAPTER TWO LITERATURE REVIEW It has been said that extreme disasters are a relatively normal occurrence in the overall experience of mankind. Through long experience humans have become mentally equipped to endure and survive catastrophes. Afte r all, a natural disaster only exists if it can be said to have affected a human society in a negative manner. In societys desire to prevent or mitigate disasters it has been noted that efforts must be initiated prior to the event if success is to be exp ected (Tobin and Montz 1997). Flood damage continues to increase in the United States despite widespread efforts to mitigate flood hazards and regulat e development in flood-prone areas. The National Weather Service (NWS) has maintain ed a relatively long-term record of flood damage throughout the United States. These reco rds are estimates of physical damage to property, crops, and public infrastructure. Estim ates for individual flood events are often quite inaccurate; however, when estimates from many events are accumulated the average of the errors become proportionately smaller (Pielke et al 2002). In 1991 United States monetary losses, as a result of flooding, were estimated at $1.698 billion. By 2001 the National Weather Service (NWS) estima ted that annual monetary damage from floods had increased to $7.158 billion. An exceptional year for floods was 1993, when losses amounted to $16.364 billion (Pielke et al 2002). In the period from 1903 to 1997 the Unites States alone has experienced nine thousand and thirteen deaths from flooding

PAGE 19

8 or an average of about 95 deaths per year (NWS 1997). UNESCO notes that during the period from 1973 to 1997, worldwide, sixtysix million people suffered flood damage (UNESCO 2001). Floods make up in excess of th irty percent of all disasters world wide, but it is the relatively few extreme floods th at are responsible for the highest amounts of damage and deaths (Tobin and Montz 1997). Clearly floods and flooding are worthy of our interest. It is the extreme flood that inflicts the most severe damage and causes th e majority of loss of human life. Extreme floods are of interest to planners, designers, a nd engineers as they relate to the expected useful life, design, and constr uction techniques of bridges, dams and other structures. Extreme floods are also of inte rest to geographers and planne rs as they relate to landuse as demanded by expanding populations (Cohon et al 1988). This interest is particularly high where the large-scale risk of loss of human life is possible. There are many types and magnitudes of di saster. When large numbers of human lives are lost it is most often caused by only a relatively few and extreme natural disasters. These disasters are usually termed severe natural disasters. On any given natural watercourse a flood of some magnitude occurs on average every 2.33 years (Dunne and Leopold 1978). Most of the time these floods cause inconvenience and some relatively minor property damage. Larger fl oods occur less often and are described as 10, 25, 50, 100, or 500interval year floods. The 10yr flood, having a 10% chance of occurring in any one year, the 100yr. fl ood, a 1% chance, and the 500yr, flood a 0.2% chance of occurrence per year. The greater the expected return period the larger the expected flood. Floods in the 100-year (1% chance per yr.) to 500year (0.2% chance per yr.) range are considered rare and extreme. Floods do however; occur at much greater

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9 average time periods such as the 1,000-year (0.1% chance pe r yr.) flood. In the United States, historic flood records do not exist fo r periods exceeding 100 years except in rare instances. This inhibits the extrapolation of flood magnitudes from historic records to extreme levels that are known to occur, but for which there are few data. Nevertheless, extreme floods are of intense interest. For this reason, the magnitude of these exceptional floods must be estimated in some way (Lane nd.). Floods of very great magnitude occur so rarely that they provide few opportunities for study. When very large fl oods do occur, physical conditions often prevent or inhibit well-designed scientific in vestigations. It is however, the extreme flood that is of greatest danger or greatest na tural hazard. Historically, floods have been the third largest cause of death due to natu ral hazards worldwide. Tropical cyclones are ranked first as disasters causing th e most deaths. It is noted th at a very high percentage of deaths due to rotating storms are caused by the flooding of low-lying areas (Tobin and Montz 1997). It should also be noted that for the last 30 years inland flooding has been the most important factor in loss of lif e (See Figure 1) caused by tropi cal storms within the United States (NOAA 2003b). High rainfall rates are not necessarily associated with high wind speeds. Many record rainfall depths have been related to less intense storms that move slowly, or stall over an area. Numerous ex amples of intense rainfall resulting from tropical storms have been recorded at consid erable distance from coastal areas. In 2001 hurricane Allison produced heavy rainfall from Louisiana to Massachusetts resulting in 41 deaths and $5 billion dollars in damage. In 1999 Floyd moved slowly along the East Coast resulting in 56 deaths of which 50 were caused by inland flooding. In 1994

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Alberto dropped 21 inches of rain in parts of Georgia, and caused 33 deaths. The year 1979 saw Claudette produce 45 inches of precipitation in Texas. Agnes (1972) caused 122 deaths and $6.4 billion in damages. Fifty-nine percent of all deaths attributed to tropical storms from 1970 to 1999 (See figure 1) have been the result of freshwater flooding in inland areas (National Hurricane Center 2002). Fig 1 Inland flooding is the cause of 59% of all tropical storm related deaths over the last thirty years. The Probable Maximum Flood (PMF) is defined as the most severe flood that is considered reasonably possible at a site as a result of rare but ideal hydrologic and meteorological conditions. PMFs are referred to as probable due to their extremely long, and necessarily unspecified, return period or probability of occurrence. It is not possible, due to the extreme magnitude and rarity of such floods, to assign a confidence 10

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11 of error to the size or the return period of an extreme flood (USGS 2002). It should be noted that it is not only extr eme floods that cause property damage and loss of life. Flood depths of only one meter at a velocity of one meter per second are considered sufficient to cause structural damage in large areas and possible loss of hu man life (Ward 1978). It appears from the existing literature that studies related to extreme flooding have not been pursued in relation to relatively small drainage basins. Extreme floods are primarily of interest in relation to the engi neering and construction of major examples of infrastructure. In these considerations the primary concern is the design and construction of the edifice such that all reasonable po ssibility of catastrop hic failure has been considered and mitigated. Th e possibility for catastrophic inland flooding, in the context of the small drainage basin, is very real. Estimating the extent of flood probabilitie s on the order of one in one thousand or lower would require extrapolation far beyond any flood or meteorologically related data set available. Of the many methods availabl e that could be used to estimate extreme floods, (Cohon et al 1988) states that there are three genera l types, the most common and widely used is the probable maximum precipi tation (PMP). The largest rainfall event that can be reasonably conceived for the regi on is converted into stream flow and a flood hydrograph is constructed. This hydrograph is termed the Probable Maximum Food (PMF) (Cohon et al 1988). A PMF is defined by Ward (1978), as the flood resulting from the Probable Maximum Precipitation (PMP) falli ng on a drainage basin when it is in a state of saturation. It is also possible to collect historic a nd paleoflood data, and use these data in flood frequency analysis to establis h a frequency curve that can be extrapolated. Paleoflood data, on the other hand, may be affected by climate change; thus the

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12 extrapolation of such data may no longer accurately represent local conditions (Dunne and Leopold 1978). As a third general method, mathematical models of extreme storms can be constructed, from which runoff amounts can be established. In the methods using historic flood data and runoff models ther e are few documented cases in which these methods have been used to estimate floods of return periods in excess of one hundred years (Cohon et al 1988). In a general sense design floods may be estimated either by what is termed deterministic methods, in which floods are seen to result from a specified precipitation falling within the drainage basin, or as probabilistic in nature, in which floods are seen as random events investigated by statistical analys is. There is little a pparent advantage to one general method over the other when attempting to estimate extreme floods. Both suffer from the same shortage of historic da ta upon which to base the estimates. Due to relatively short length of histor ical records, which record less than one hundred years of flood data, both methods may be forced to use a short range of data to extrapolate a long flood return period (Ward 1978). The probable maximum flood in a region can also be depicted by a graph on which recorded maximum floods are plotted ag ainst drainage area. Smooth curves enveloping the plotted points (envelope curv es) are drawn such that all of the points indicating maximum floods are below the curv e. Since the curve represents a flood at least as large as the largest historic flood, probability levels cannot be assigned. It is thought that envelope curves encompassing th e largest flood events in a region tend to become more reliable as the area and pe riod of observation in crease (Phillips and Hjalmarson 1996). This type of graph has been generated by Crippen and Bue (1977)

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13 for seventeen regions within the Conterminous United States, and is used by the United States Geological Survey (USGS) and othe rs to estimate Probable Maximum Floods for drainage basins of comparable size. Probable Maximum Floods are considered as engineering factors related to large dams or bridges, or more recently for evacu ation plans for coastal areas threatened by tropical storms (USGS 2002). The five hundr ed-year flood is usually the largest flood used as a measure of extreme flooding by govern mental agencies. It is chosen primarily as a result of economic considerations. Fl ood-plains are desirable locations for human occupation, but floods are costly in terms of loss of property and loss of human life. At some point the desirability of flood-plain occ upation begins to outwei gh the potential cost in property and lives. The Federal Emer gency Management Agency (FEMA) defines this point at the level of the one hundred-y ear flood. Areas outs ide the one hundred-year flood zone are considered suitable for occupa tion even though it is expected that at extended periods of time some of these areas will experience flooding (FEMA 2003). Major structures such as large or important br idges, large dams, or levees protecting large populations are constructed to withstand the five hundred-year flood. These areas are considered more vulnerable for increased human mortality due to high population exposure (USGS 2002). There is a considerable difference between the expected runoff created by a five hundred-year flood and the runoff created by a Probable Maximum Flood. The 500-year flood-peak discharges will likely be consider ably less than the e nvelope-curve values, assuming that several watersheds in a given region have experienced at least one flood exceeding the 500-year value during the period of data collection. For example, the 500-

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14 year flood of 12,800 cubic feet per second at the Fenholloway Ri ver (Florida) is relatively small compared to the Probable Maximum Flood envel ope-curve value of 101,000 cubic feet per second for the same loca tion (USGS 2002). While flood events of this extreme magnitude are very rare, they are not totally unexpected; nevertheless they are not addressed in existi ng literature in relation to small drainage basins. West Central Florida is statistically due to experience a major tropical storm. The state of Florida has experienced fifty-seve n hurricanes from 1900 to 1996. Twenty-four of these storms were category three or highe r on the Saffir-Simpson scale. On average Florida has been the landfall site for a major tropical storm every four years for the last century (NCEP 2003). In the United States inland flooding ha s been the primary cause of tropical cyclone-related fatalities over the past 30 years (NOAA 2003b). Precipitation is generally heaviest with slower moving stor ms (less than 10 mph). The heaviest rain usually occurs to the right of the cyclone track in th e period 6 hours before and 6 hours after landfall. However, storms can last for days, depending on the inland weather features with which they interact. Large amounts of rain can occur more than 100 miles inland where flash floods and mudslides are typically the major threats (NOAA 2003b). The record amount of rainfall for the Stat e of Florida in a tw enty-four hour period is 38.7 inches (See figure 2). This record ra infall was due to an unnamed hurricane that lingered just off shore of Yankeetown Flor ida for several days in 1950 (NOAA 2003c).

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Maximum 24-hour Precipitation in the United States Fig. 2 The record precipitation for the state of Florida is 38.70 inches in 24 hours. Second only to the 43.0 inch record in Texas. West Central Florida has been affected by tropical storms on the average of once every 3.77 years in the last one hundred and thirty two years. Hurricanes have passed within forty miles of Tampa Florida, on average, every thirty-three years (Unknown.a). In spite of the seemingly large number of tropical storms that have passed in close proximity to the study area, the general public is not aware of the potential extent and duration of the inland flooding that would occur in a significant storm event. Eighty to ninety percent of the population now living in hurricane-prone areas has never experienced the core of a "major" hurricane (NOAA 2003a). 15

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16 Flooding, has historically, been studied after the event ha s occurred. Since a severe storm event will occur, it seems r easonable to attempt a study that models the inundated area prior to the event rather than wait to determ ine what occurred after the fact. It appears that the literature related to flooding, severe flooding, hurricane induced flooding, etc. has not addressed the inundate d area resulting from a Probable Maximum Flood event in drainage basins of relatively small size. Post flood studies have been pursued in numerous instances in efforts to provide learning opportunities from a hi storical perspective. In general these efforts while successful in the physical sense have not me t with considerable success in areas of population education and flood mitigation. The same reside nts often repopulate floodplain areas, event after event. Extreme flood events are not totally explained by physical processes. Disasters of this type are as much related to social and cultural forces than they are to hydrological and me teorological events. Nevertheless, there is little argument that the physical characteri stics of extreme events are important (Tobin and Montz 1997). It is not expected that a study of potential flooding will materia lly alter the human desire to rebuild or remain in the area, but in areas that are unde r development a visual depiction of anticipated flooding may impact social and cultural decisions. The post flood study that is usually done will be doubly useful in comparison with this examination of potential flooding. The advent of computers a nd related software has removed many of the barriers to quantification. Quantification now has a new outlook; landscapes formally impossible to generate (within reasonable cost and tim e constraints) can be produced in minutes by

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17 Geographic Information Systems (GIS) software Calculations that in the recent past would have taken a team of mathematicia ns weeks or months can now be done in seconds. Combined with software algorithms that can generate filled contour maps as well as the ability to overlay map transparencies, GIS technology has given new life to quantitative positivist methodology (Johnston 1997). Precipitation models are now available that can be used in conjunction with relatively new flood models that allow predictions of flood extent based on cha nnel elevation. Such a study would have considerable value as an educational tool us ed to enlighten the public in way that may save lives or mitigate physical damage by allowing informed site selection for homes or businesses (Jaeger 2002). ABOUT THE AREA There are nearly 45 million permanent re sidents in the area along the United States coastline where hurricanes are most prevalent. The area experiencing the most growth has been the state of Florida, but extensive growth has been seen from Texas to the Carolinas (NOAA 2002). The last hurricane to pass within twenty miles (direct hit) of West Central Hillsborough County was an unnamed, category two, storm (See figure 3) that occurred in 1921 (unknown.b). At that time the population of Hillsborough County was approximately 9% of its present size (Census 2003). The landfall of a major tropical storm on the West Coast region of Florida will have a major impact resulting in severe inland flooding. Etheridge (2001) notes that forty-eight deaths and nearly $3 billion worth of propert y damage occurred in inland communities as a result of Hurricane Floyd. In the thirty years prior to 1999, six hundred

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18 deaths have been attributed to hurricanes and tropical storms. Eight y two percent of these deaths were by drowning and the American Meteorological Society states that more than half of these drownings occurred in inland counties while coastal storm surge accounted for six fatalities. It is Etheridges (U.S Representative and a member of the House Science Committee) opinion that inland flood forecasting and warnings must be improved. In West-central Florida several factors cont ribute to this hazardous environment. The relatively flat topography, Karst drainage, and extended period of time that has elapsed since the last serious inland flood combined with the extensive popul ation growth within the area tend to increase the potential for a major disaster far in excess of what is generally expected. Areas that appear to be excellent housing or business locations for the exploding populations are of ten, in reality, lakes that ar e usually dry due to Karst topography. Many of these areas will be subm erged in a Probable Maximum Flood. The lack of relief in the area i nhibits the rapid runoff of surf ace water. The Florida climate entices retirees to relocate into the area in la rge numbers. Many of these individuals have minimal knowledge of Karst topography. Waterfr ont property is also highly desirable as a location for home construction. In general, pr operty values are lower in Florida than in many areas of the Northeastern States. These enticements lead to development of land areas that appear to be suitable in relativ ely dry conditions. Many of these areas have been subdivided that begin to exhibit partial flooding at times of s lightly above average rainfall amounts. These areas react to the increased urbanization and its attendant reduced infiltration capacity and increased overland flow, due to road paving and building construction, by flooding of the natu rally low areas within the development.

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Often this flooding does not occur for several years after the development is completed. The homeowner is surprised by the unexpected flood and seeks redress from the local governmental agency. Thus the County is often saddled with the considerable cost of mitigating what is a normal phenomenon. Fig.3 An unnamed category 2 hurricane passed within 20 miles of the study area in 1921. Source: Unknown,(b) 2003. 19

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20 The general lack of awaren ess related to severe inland flooding may be in part, due to a dearth of experience on the part of local government concerning severe storm event precipitation amounts. Mo re likely local and state governments are following the recommendations of the Federal Emergency Management Agency by allowing construction on land deemed to be outsid e the one hundred-year flood-plain. This may have resulted in political actions by local government in issuing building permits for vulnerable areas that exhibit a lack of rapi d natural drainage due to Karst topography and little relief. An example may be the relative ly new subdivision at the South end of Lake Wheeler (See figure 39). The fact that this area is a few tenths of a foot above the calculated one hundred-year flood may be of little solace to homeowners if that level is even slightly exceeded. The issuance of a building permit implies that some agency has determined an area is suitable for a particular use, this expectation can result in the population being unprepared fo r extensive inland flooding. Probable Maximum Flood (PMF) curves as defined by Crippen and Bue (1997) will be used to determine the magnitude of a severe flood on the study area, a small drainage basin in West Central Florida. As populations increase and property at higher elevations becomes more expensive and less available, land at lower elevations becomes more desirable. Flooding of relatively sma ll drainage basins has been historically of minor importance due to their usually sparse population. Investigati ons related to very large flows have tended to concentrate on la rger river basins th at contain densely populated areas. In an effort to establish a method in which a very large or maximum flood could be estimated for smaller basi ns, Crippen and Bue (1997) extracted 883

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21 extreme flood sites from thousands of recorded floods throughout the conterminous United States. The chosen sites drain areas less than 10,000 square miles. The sites were then grouped into regions having sim ilar rainfall intensity and physiographic type (See figure 4) (Fenneman 1931, 1938). Extreme floods from each region were then plotted on graphs and envelope curves were calculated that allow estimates of maximum flood as they relate to basin size. Typical ly these curves indicate flood volumes two to three times larger than the largest flood record ed from similar sized basins in the region. Due to the extreme magnitude of these floods and corresponding rarity no return period can be calculated (Crippen and Bue 1997). The Probable Maximum Flood (PMF) is defined as the flood that may be expected from the most severe combinati on of meteorological and hydrologic conditions that are reasonably possible in a particular drainage area (Ohi o nd). The Probable Maximum Flood (PMF) results directly from a Probable Maximum Precipitation (PMP) event. Extreme events such as floods resulting from dam failures or ice jams are not considered Probable Maximum Floods. Drai nage areas with the same Probable Maximum Precipitation may have different Probable Maximum Floods. This is possible due to the differing characteristics of drainage basins. Characteristic s affecting Probable Maximum Floods include channel slope, so il type, landuse, size and shape of the watershed. These variables must be take n into consideration along with Probable Maximum Precipitation. Thus the Probable Maximum Flood, rather than the Probable Maximum Precipitation, must be used as a de sign criterion for critical areas. Both meteorological methods and historical records are used to determine the greatest amount of precipitation that is theoreti cally possible within a region. Th e historical data consist of

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22 precipitation amounts measured at rain gages throughout the region, or rainfall measured in a region with similar meteorological and t opographical characteri stics. Rainfall data gathered in either manner can be maximi zed through "moisture maximization". Moisture maximization is a process in which the maximum possible atmospheric moisture for a region is applied to rainfall data. This incr eases the apparent rain fall depths, bringing them closer to their potential maximum, Once the Probable Maximum Precipitation has been determined a flood hydrograph can be c onstructed that represents the Probable Maximum Flood (Ohio nd). The consequences of a prolonged or ex treme precipitation event are not well understood by the general populous, and it is expected that inla nd flooding during a Probable Maximum Flood will be so severe th at property damage and loss of human life may be high. The magnitude of this expected ev ent is such that an effort should be made to develop a predictive procedure that will encourage mitigation prior to extreme flood events. It is expected that a graphical depiction of areas inundated as a result of an extreme flood would be of interest to planners, civil engineers, and elected officials responsible for the development of businesses and subdivisions that may be in potential danger. This study will not attempt to establish a flood extent from a precipitation event. It will instead use flood flow velocities and volumes established by the Probable Maximum Flood (PMF) curves established by Cr ippen and Bue (1997) as they relate to the physiographic regions in the United States (See figure 4).

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Physiographic Regions of Maximum Flood Flows Fig.4 Regions within the United States that have similar meteorological and topographical characteristics. THEORY The study will use a moderate version of positivism known as Post-positivism, Critical Realism. This version of positivism has served as a replacement for Logical Positivism. Logical Positivism (logical empiricism) is based on the verification theory, which holds that statements or propositions can be meaningful only if they can be, without exception, empirically verified. In Post-positivism, Critical Realism, the concept of complete verification would be replaced with the idea of gradually increasing confirmation as a result of numerous successful experiments or models (Trochim 2000). 23

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24 Logical empiricism holds that all knowledge begins with observation. This leads to empirical generalizations among observable phenomenon. As ideas progress, theories are formulated deductively to explain the gene ralizations, and new evidence is required to confirm or reject the theories (Malhotra 1994) It has been argued th at if the positivist version of verification is taken to mean the complete establishment of truth, then universal statements could never be verifie d, and truth could never be determined (Peet 1998). However, using Post-positivism, Critical Realism, statements may be confirmed to be adequate for practical purposes by the accu mulation of successful empirical tests. Thus science can progress through the accu mulation of such tests (Trochim 2000). In addition to the problem of verifi cation, Logical Empiricism and Postpositivism, Critical Realism both encounter difficulties due to the insistence that science rests on the basis of uninvolve d objective observation on the pa rt of scientists. There are at least two problems here. The first is that observati ons are always subject to measurement error and social and political pressures often colo r results. The second problem concerns the fact that observation is preceded by theory, and theory often leads to results that support the theory. This calls into question the lack of impartiality on the part of researchers, and the claim that sc ience is based on objectiv e observation (Malhotra 1994). It is realized that the st udy of an anticipated event cannot be classified as scientific in the Positivist sense. Followi ng a strict Positivist methodology would require the actual observation of the flood event. The quantification of this anticipated event will be estimates from computer models, (based on regionalized maximu m flood data) rather than actual flooding (based on recorded data). This t ype of study is however now

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25 possible due to the development of advanced flood models. These models have been tested against available historic data to the extent that they have been determined to be adequate for practical purposes. This is an advanced outlook on flooding that is relatively new, but has been used on large drai nage areas such as that of the Rhine River (Jaeger 2002). GEOGRAPHIC INFORMATION SYSTEMS The investigator of the p hysical study must keep in mind the limitations of GIS generated information and refrain from treating these data as highly accurate due to the computers ability to deliver decimal place re sults. These results must be accompanied by well-defined explanations as to the range of accuracy in which the informatin should be considered (Lo. 2002). The researcher has an et hical responsibility to present the study in such a way that the conclusions reached are not expressed as hard facts, but as estimates based on verified information. Conclusions must have been arrived at via a specified path that is well documented, such that others can evaluate the endeavor in light of their own experience or experiments (Peet 1988). Geographic Information Systems (GIS ) are computer based systems for managing geographic data and using these da ta to solve spatial problems. A more general statement is that GI S allows data to be changed into information (Lo. 2002). In general GIS is used to create map layers that can be viewed at various levels of transparency. These layers which may cons ist of a base map depicting the political boundaries of an area overlain with a layer showing road lo cations, a drainage layer, a topographical (contour) layer, a nd a land-use layer. Various analyses may be carried out

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26 comparing the effects of one layer upon anothe r. For example one layer may be used to filter another layer. The political layer may be used to filter the land-use layer such that it is possible to list what land-use parcels are c ontained within a partic ular political (county, city, flood zone, zip co de) boundary (Lo. 2002). Geographic data are represented in either ve ctor or raster format. Vector data is delineated by points, lines (arcs), or polygons. Vector da ta are referenced by x-y coordinates related to a specific map projec tion. Raster data is delineated by sub dividing the general area in que stion into small square areas. Each of these small squares represents a particular attribute. Data in vector format lends itself to the geographical analys is of individual objects. It is most suited for use in applica tions such as transpor tation planning, natural resource management, cartogra phy, and land title information. Whereas data in raster format is most useful in applic ations that relate to surfaces such as temperature, rainfall, elevation, landuse, or environm ental considerations. Rast er data usually relates to relatively large areas at the re gional or national level, whil e vector data lends itself to relatively smaller areas at the local level. Rast er and vector data can be displayed in the same map projection. This allows layers with point, line, surface and polygon data to exist in the same map (Lo 2002). The ability to store, retrieve and analyze spatial data makes GIS unique among data base management systems (DBMS). GIS data were stored using what was termed a geo-relational data model. In this model, gr aphical data were stored in one database that referenced containment, connectivity, and ad jacency, while at the same time attribute data were stored in a separate but related database. More recently GIS uses an object-

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27 relational model as a storage a nd retrieval method. In this model graphical and attribute data are stored in the same database, thus simpli fying search and retrieval. In this model attribute data are stored in a modified relati onal database and graphical data are stored in an added column, often named shape. This shape column contains references to geographical data, for example, data type, number of points, x-y coordinates. Software is designed to search and access these shape references, and allow the manipulation of data by activities such as insertion, deletion, or reformatting. Data processing is also supported that allows display, computat ion, summarization, and plotting (Lo. 2002). The results of this thesis will be inco rporated into a Geographic Information System (GIS) to enable an alysis related to human occupation. Although it should be noted that extensive analysis is not the focus of this endeavor nevertheless some analysis will be demonstrated for the purpose of example. RESEARCH QUESTIONS Is the easily acquired and inexpensive flood program, Hydr aulic Engineering Centers River Analysis System (HEC-RAS), a viab le solution to flood inundation on a small drainage basin? What is the area of the study basin that will be inundated by a Probable Maximum Flood? What are some of the significant effects of a Probable Maximum Flood on the study area?

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28 CHAPTER THREE STUDY AREA The study site is a sub-basin within the Selfer Drainage Basin located in Hillsborough County Florida. The location of this study area was selected primarily due to its physical characteristics and accessibilit y. West Central Florida is chosen as the general physical region because it exhibits re latively unique Karst topography with little topographical relief, and a climate with a po tential for wet and prolonged storm events. Drainage in Karst topography is mainly accomplished by direct infiltration into a limestone substratum or by numerous short creek s that empty into lakes that have little or no outlet. The surface water in this topography in filtrates into the limestone substrata or evaporates. There are few major rivers that carry large amounts of surface water to the sea. The Karst topography thus insures that surface water recedes slowly. Outflow is often a relatively small fact or in floodwater removal. The local, political, region (county) reside s in the large physical region of West Central Florida. The populace is composed of a mostly economic middle class, English speaking population. The area under study (the particular area of Hillsborough County) is to be considered more than an area surrounded by lines, it is the product of human history and as such is con tinually changing (Pudup 1988). It is recognized that regions are always incomplete and ongoing and that changes occur simultaneously and at different scales. Processes of geographic a nd social change are continually reshaping

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29 regions, and the regions are constantly adju sting to change (Bosman 2000). Thus, the area under study will be investigat ed in a manner such that any conclusions reached will be considered valid only for the specific and relatively short time during which no significant geographical, social or cultu ral changes occur (Johnston 1997). In a large sense the spaces pertinent to this proposed study may be seen as a nested set of social, political and physical regions. They begin with the largest region possible within the definition of geogra phy, the earth, then North America, the Southeastern United States, Florida, We st Central Florida, Hillsborough County, and finally the relatively small area of study, name d the Selfer Drainage Basin (Baker Canal) near the center of the County. (See figure 5) The level of existing ground water has a major effect on floodwater removal. High ground water levels prior to a storm even t will result in lower infiltration rates, increased flooding, and slower recession levels (Owen 1998).

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Small Scale Location Map Fig 5 The study area is located in West-Central Florida in the County of Hillsborough. Data Source: Hillsborough 2002. 30

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SELFER DRAINAGE BASIN (Baker Canal) A Probable Maximum Flood study is particularly suited to West Central Florida. This area is statistically overdue to experience a major tropical storm event. It is geographically a Karst region that has a moderately dense population that exhibits a mix of urbanization and agriculture. The general study area is in a 30 sq. mi. catchment located in central Hillsborough County (Selfer drainage basin) (See figure 6). Selfer Drainage Basin with Limits of Specific Study Area Indicated Sc N Fig. 6 Selfer Drainage Basin Scale 1in. = 3.5mi. The Selfer Drainage Basin is approximately 7 miles South-east of the University of South Florida. The relief, while relatively minor in the region is particularly flat along the North-South axis of the basin. East to West the relief is much greater and varies from a 60ft 31

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32 elevation at the West divide to 40ft +/at th e outflow canal, and then to 70ft +/at the eastern divide. This produces an elongated and flat-bottomed bathtub shaped basin with one outfall channel exiting to the North. In ad dition to the minor relief there are four standing lakes and one ephemeral lake within the basin that attenuate the water flow. Outside the basin, runoff passes through a large wetla nd area as it ente rs a large lake (Lake Thonotosassa) several mile s North of the basin where it is further attenuated by a control structure (dam) prio r to entering the Hillsborough River. The Hillsborough River then empties into Hillsborough Bay, which connects to the Gulf of Mexico. The Southwest Florida Water Management District (SWFWMD) indicates that the average stage for Lake Thonotosassa is approximatel y 35.3 ft. This stage can increase to 36.2 ft for the 2.33 year flood event, and further incr ease to 42.0 ft during the 100-year flood event (Hillsborough 2002). SPECIFIC AREA The specific area of investigation will be the area of the Self er (Baker Canal) Drainage Basin from Muck Pond Rd. South to the CSX Rail Road embankment North of State Hwy. 60. There is no natural flow of su rface water from the area South of the RR embankment into the Selfer basin, and Nort h of Muck Pond Rd. the topography flattens and other basins contribute runoff such th at modeling becomes uncertain (See figure 7).

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An Enlarged Map of the Sub-Basin within the Selfer Drainage Area Fig. 7 Note the R.R. embankment that delineates the Southern end of the study Area and Muck Pond Rd. lining the Northern end of the Study Basin. Source: Hillsborough 2002. 33

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34 STUDY AREA LAKES The four major lakes that are within th e study area basin include Lake Valrico, Long Pond, Lake Hooker and Lake Weeks. La ke Valrico is 124 acr es in extent and drains a sub-basin of approximately 1055 acres The deepest area (9ft) is in the center of the lake. The average depth is 4 feet and the average lake level is 44.0 feet above sea level. Long Pond is 55 acres in area, and dr ains a sub-basin of 726 acres. The lake has an average depth of 7 feet and the average lake level has been 41.3 feet. Lake Hooker and Lake Weeks are both about 53 acres in area Lake Hookers sub-basin covers about 890 acres with the historic lake level at 42.5 feet. The sub-ba sin for Lake Weeks is much smaller at approximately 298 acres, and the av erage water level has been 41.2 feet. (See table 1 and figure 8) There are numerous sma ller lakes and ponds in the Selfer basin that are both natural and manmade (Hillsborough 2002). Table 1 Study Area Lakes Lake Valrico Long Pond Lake Hooker Lake Weeks Acres 124 55 53 53 Drainage Area 1055 726 890 298 Avg. Depth 4 7 N/A N/A Max. Depth 9 9 10 7 Average Elev. 44 41.3 42.5 41.2 Lake Data at Normal Water Levels

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Fig. 8 This map depicts study area lakes and surrounding areas of low elevation. The low areas surrounding Lake Hooker are subject to flooding during normal precipitation events. 35

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36 LAND-USE The Selfer drainage basin can be characterized as being made up primarily of rural and rural-residential la nd-uses. Land-use is ne vertheless, diverse, with approximately thirty-three percent of the basi n engaged in various agricultural activities, while nearly twenty-nine percent is residentia l. Five percent of the basin is subject to frequent flooding (See table 2). The majority of the resident ial landuse is low to medium density. Most of the commercial areas are loca ted near the major roads such as Interstate 4, and State Road 60 (Hillsborough 2002). Following page contains a Landuse map of the study area, (See figure 9). Table 2 Landuse Acres Percent of Total Agriculture 4495 33.5 Residential 3941 29.3 Forest 1385 10.3 Open land 1095 8.1 Commercial 891 6.6 Wetlands 698 5.2 Water 690 5.1 Mined land 148 1.1 Underbrush 97 0.7 Total 13440 100 Landuse by percentage within the St udy Area. Data dated 1999 Source: Hillsborough 2002

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Landuse in StudyArea Landuse within the Study Area Basin Fig.9 This map graphically indicates the large amount of Residential and agriculture landuse. Data dated 1999. Source: Hillsborough 2002 FUTURE LANDUSE The Selfer drainage basin is not heavily developed at this time. The Hillsborough County Planning Commission is predicting increased development in the near future. It is expected that much of the open or agricultural land (41% of the total land area) will be 37

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developed into residential and light industrial or commercial use (Hillsborough 2002). (See figure 10) Fig. 10 Open and agricultural land areas are slated for development. Data dated 1999. Data Source: Hillsborough 2002 38

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ZONING The area of interest is zoned by Hillsborough County as is seen in figure 11. Zoning by percent of area is listed in table 3. Fig. 11 The majority of land in the study area is zoned for agriculture or residential use. Data Source: Hillsborough County. nd. 39

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40 Table 3 Study Area Zoning Acres Percent of Total Area Residential 25.9 Commercial 3.1 Agricultural 71 Total 100 Study area zoning by percent of land area. Source: Hillsborough County. nd. STUDY AREA CHARACTERISTICS The climate of the Selfer drainage ba sin, humid subtropical. Annual average precipitation is around 53 inches. Approximately 60% of this total falls during the fourmonth rainy season that extends from June thr ough September. This is a time when the summer heat allows rising thermals inland of the peninsula. These thermals encourage a Westerly sea breeze that meets the moist Easterly moving across the State from the Atlantic Ocean. The collision of these front s results in the formation of cumulonimbus clouds that develop into the nearly daily thunderstorms that cr eate Central and South Floridas rainy season. These summer events which can be very localized, are highly variable in both intensity and volume. The larger thunder storm events and those associated with tropical systems can cause flooding in areas where the topographical relief is small. During the winter months rain fall is associated with the cold fronts that move from the northern part of the country and travel south through the region. It should be noted that some of the largest single ra in events and associated flooding have occurred

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41 in the winter and spring months. These excep tional rainfall events are more often seen when the El Nino-Southern Oscillatio n is in effect (Hillsborough 2002). TEMPERATURE The annual mean temperature in Hillsborough County is 72 F. The average monthly temperature ranges from a low of approximately 60 F in January to a high of approximately 82 F in August. Typical summer temp eratures range from lows in the high 70's to afternoon highs that reach in to the high-90's, but rarely exceed 100 F. Summer humidity that often reaches 90 percen t and can increase the apparent heat index. The low winter temperatures generally range from above freezing to the 40's, and only occasionally drop into the low 20's or high teens. High winter temperatures generally reach the upper 60's or low 70's for most of the winter season, but tend lower during passages of numerous cold fronts (Hillsborough 2002). EVAPOTRANSPIRATION Estimates of actual evapot ranspiration rates vary between 39 and 48 inches per year. Tampa Bay Water (an intergovernmenta l agency) estimates that lake evaporation rates average approximately 56 inches per year. Potential evapotranspiration estimates range as high as 78 inches per year (Hillsborough 2002). GEOLOGY The Selfer drainage basin lies in an area of Karst topography. At depth there exists a thick layer of conso lidated but highly fractured carbo nate rock. At the surface lies

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42 a varying depth of unconsolidated silt, sand and clay. These surface deposits range between twenty to fifty feet in depth (See table 4 and figure 12). The underlying carbonate rock is composed of limestone and dolomites formed in the Tertiary period. In descending order, the various limestone strata are named as follows. Tampa Member of the of the Arcadia Formation of the Hawthorn Group, Suwannee Limestone, Ocala Group, Avon Park, Oldsmar, and Cedar Key Formations. A lithographic change from limestone and dolom ite to a sequence of gypsiferous dolomite begins in the lower portion of the Avon Park Formation and continues into the Oldsmar and Cedar Key Formations. The top of this lithologic change marks the middle-confining unit of the Floridan aquifer system. The middl e confining unit is gene rally considered the base of the freshwater production zone of the Upper Floridan aquifer Hillsborough2002). Table 4 Soil Types Acres Percent of Total Fine Sand 0 to 12 degree 4901 36.7 Water 498 3.7 Fine Sand Depressional 1397 10.5 Fine Sand 6549 49.1 Total 13345 100 Source: Hillsborough 2002

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Study Area Soils Fig. 12 This map graphically indicates the fine sand composition of the soil within the study area. Data Source: Hillsborough 2002 43

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44 Surficial Aquifer The majority of the surficial aquifer is co mposed of various grades of medium to fine-grained sand. This aquifer averages a pproximately 30 feet in depth, but depth is variable as a result of the Kars t nature of the region. It is of considerable interest that the water table is relatively close to the surface, us ually not more than several feet deep. This fact limits the infiltration capacity of the basin and results in early saturated overland flow during rainfall events. Infiltration is the primary influence on water table elevation, with annual highs in most years occurri ng during the wet season and annual lows occurring near the end of the dry season. Ground water generally flows from the Northeast toward the Southwest across the Self er drainage basin. (See figure 13) The surficial aquifer is partly isolated from the Upper Floridan aquifer th at lies beneath it by a layer of mixed clays and silts. This layer of confining material is discontinuous due to the karst topography of the area. Numerous areas exist in whic h the clay layer is absent or perforated such that water from the surfic ial aquifer is able to percolate downward into the Upper Floridan aquifer (Hillsborough 2002).

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Fig. 13 This map depicts the surface contours of the Upper Floridan Aquifer. Note the converging contours in the vicinity of the study area. Source USGS 45

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BAKER CANAL PICTURES The following pictures depict the Baker Canal at various locations beginning at the study area out-fall and progressing upstream toward the headwaters of the basin. These photographs are dated September 2003. Baker Canal North of Muck Pond Rd. Pic 1 Note the pasture area at upper right of the photograph. This area is subject to flooding beginning at flow rates of only 300cfs. Hillsborough County has dredged this part of the Canal in 2002. Water level is slightly higher than yearly normal at approximately elevation 38.5ft. 46

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Baker Canal South of Muck Pond Rd, Pic 2 Note the vegetation growth along the banks. This area of the Canal has not been dredged as recently as the area North of Muck Pond Rd. This area also easily overflows its banks. In September and December 1997 the Hillsborough County Engineering Dept. recorded an estimated 50yr flood at this location. 47

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Baker Canal North of State Road 92 Pic 3 This area has been dredged in 2002. Water level is normal for September. 48

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Baker Canal South of State Road 92 Pic 4 Note the lack of bank side vegetation due to dredging. Water level is at normal levels mostly due to ground-water seepage. Flow rate is approximately 200cfs. 49

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Baker Canal under County Road 574 Pic 5 The flow seen in this photograph is normal and due to ground water through-flow from the basin. The picture is taken from the RR Bridge just South of County Rd. 574. Both of these roads are over topped by the Probable Maximum Flood. 50

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Lake Valrico Water-front home. Pic 6 Lake level is normal for the end of what is known as the rainy season. 51

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Lake Valrico New home construction. Pic This is not flood stage. The lake level is normal for September. 52

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53 CHAPTER 4 METHODOLOGY This study is methodological investigation that seeks to determine if an extreme flood area can be successfully estimated usi ng an easily and inexpensively acquired flood program. The study seeks to produce this extr eme flood estimate in a small (22sq.mi.) drainage basin and map this flood in a way that enables analysis. Exte nsive analysis is not a goal of this investigation. Every effort to obtain the most up to date input information was made as it is realized that erroneous data may produce propagation errors that could have a detrimental effect on the generated flood areas. A relatively small percentage error in a base data may affect final re sults in a cumulative manner. As with any computer model, the limitations of the program and its underlying hydraulic computations must be understood. Informa tion generated cannot be treated as inviolate because of the apparent accuracy of calculations (Hoggan 1997). It must be repeated that this study did not attempt to establish a flood extent from a precipitation event. The st udy did use flood flow velocities and volumes established by the Probable Maximum Flood (PMF) curves for physiographic regions as defined by Crippen and Bue (1997). (See figure 4)

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54 DATA ACQUISITION The study focused on potential flooding due to a rainfall event such as a slow moving tropical depression or hurricane. As is common w ith hydrological studies a good deal of quantitative data was amassed. The area of the drainage basin was determined from USGS quadrangle maps. Contour and Digital Elevation Models (DEMs) of the basin, profiles and cross-sections of the cha nnels, and lake levels, were procured from Southwest Florida Water Management Di strict (SWFWMD) and Hillsborough County records. Records of historic flows and their accompanying rainfall events have been collected along with ground water flows and water table elevations. Bridge opening dimensions, culvert type and size, and ch annel conditions relate d to Manning numbers have been collected by field survey. Roadwa y elevations were established from profiles developed by the Hillsborough County Engineer ing Department. Roadways will act as weirs when overtopped by floodwat ers. Data related to the magnitude of the 100, and 500yr. flood peaks were gathered along with Probable Maximum Flood peak flows from Crippen and Bue (1997). A rating curve (flo w in relation to stage) is also under construction at the Muck P ond basin outfall (see Fig 19). A basic data requirement for this type of study is an elevation data set that can be used to create a Triangulated Irregular Network (TIN). The Hillsborough County Engineering Department, Stor m Water Division provided a di gital two-foot contour set that covered a large portion of Hillsborough County (See figure 15). This data set

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55 included road elevations. Normal lake su rfaces and bottoms were digitized where necessary. This contour information was gather ed from various sources and surveys done over a period of years by Hillsborough County, Southwest Florida Water Management, and private surveys. A much better, one foot ortho corrected Lidar, data set exists but was not available for this investigation. Small areas that were deficient in elevation data were overlaid with a five-foot contour data set (S ee figure 16,17). Two-foot contour lines with values within one foot of the five-foot cont ours were then digitized following the fivefoot contour line shape. While this proce dure did induce some error into the two-foot contours, the area of absent data is minimal a nd the error must be less than one foot. This error is deemed acceptable due to the small physi cal area in relation to the data sets over all size. The final contour data set used in the study appears in fi gure 18. This data set was used to create the Triangulated Irregular Network (TIN) that the flood program used to determine the hydraulic head between cross-sections along the channel.

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N ote: Areas deficient in Contours Two Foot Contours of Study Area Fig. 15 The arrows indicate several areas in which the two foot contours are absent. Source: Hillsborough County 56

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Five Foot Contours of the Study Area Fig16 Five foot data set used to digitize contour lines into the two foot contours such that they could be used by the USGS flood program. Source: Hillsborough County 57

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Five Foot Contours Overlaying the Two Foot Data Set Five Foot Contours Superimposed over Two Foot Contours Fig-17 The two foot contours (Black) falling within one foot of elevation of the five foot contours (Red) were digitized following the Red 5ft contours. Source: Hillsborough County Figure 18 represents the final two-foot contour data set. An area to the North of the outfall (downstream) has been included. The flood program requires additional data downstream in cases where water surface boundaries are unknown. In such cases the 58

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Digitized Two Foot Contours Fig Two foot contours with data gaps filled and an area to the North added. Source: Base data Hillsborough County program user must estimate a water surface elevation. This estimate induces an error in the vicinity of the estimate. Thus, the estimate must be made at a distance sufficiently downstream such that the program will have had time and distance to correct the 59

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60 computations at the area of interest, whic h in this case is the outfall of the study area (Brunner 2002). For a complete discussion of the process by wh ich the extent of the flood surface is determined please see Chapter Five Computation Procedure. GENERAL METADATA The Probable Maximum Flood (PMF) has been established within the state of Florida from an analysis of major floods im pacting Florida and the extreme Southeastern United States. Relatively long historic reco rds exist for this area of generally low geographic relief. Transposition of these data is possible from basins having historic records to similar basins where major storms of the same type have a similar probability of occurring (Ward 1978). Factors such as homogeneous regions having few topographical or meteorological anomalies te nd to allow the transposition of weather related data. The Probable Maximum Flood (PMF) will be established from flood-envelope curves developed by Crippen and Bue (1977) and Crippen (1982). The maximum flood experienced at 883 sites throughout the cont erminous United States have been grouped by region, physiographic type (Finneman, 1931, 1938) and regional rainfall intensity as defined by the US Weather Bureau 1961. Thes e extreme floods have been graphed and envelope curves computed that allow estimat es of maximum floods to be made at other drainage basins within the appropriate re gion. These curves approximate the maximum flood-peak discharge that has been regiona lly experienced for a given size watershed. Basins range in size from 0.2-sq. mi. to 10,000-sq. mi. (Crippen and Bue 1997).

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61 Canal profiles and historic lake levels have been established by County surveys. These data were used to establish the percen tage fall per mile of the drainage canal. Precipitation would be expected to be reasonably consistent over the surface of this relatively small basin due to the high volume of rainfall being modeled. For the purpose of this investigation rain fall rates are high and of relatively short duration. As a result evapotranspiration will be a minimal factor in flood-wave generation. Infiltration will also be minimal due to the normally high le vel of the Floridan aquifer throughout the drainage basin and the fact that Proba ble Maximum Floods are predicated on the assumption that basin surfaces are saturated prior to the event. Figure 19, compiles recently collected data from the Baker Canal that relates stage to flow at the Muck Pond Road Bridge (basin outfall). Historic stage data is available but corresponding flow data has not been collected. POSSIBLE PROBLEMS Runoff into the channel will be high for th is basin, but due to the very low relief along the channel, quick channel runoff will not provide substantial reduction in peak flood levels. Two drainage basins just North of the Muck Pond Road Bridge flow in an East to West direction. Relief along this ax is is on the order of ten times that of the

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Stage Verses Flow Rate at Study Area Outfall Fig. 19 Note the highest flow of 257cfs at elevation 39.65ft. The road surface Elevation is only 43.96ft. Selfer (Baker Canal) Basin, and runoff from these basins enters the same channel as the Selfer basin. During periods of high runoff it is possible that a hydraulic head develops at the confluence of the Selfer basin and basins to the North. Outflow from the Selfer (Baker Canal) basin could be reduced at these times and it is possible that at the very high flows that are being modeled, back-flow conditions may exist for intermittent periods 62

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63 (Hillsborough 2002). In addition to the above mentioned flow restrictions, the bridge opening at Muck Pond road is relatively small which will cause the road surface to act as a weir at very high flows. Under these condi tions Hoyt and Langbein (1955) note that the basin flood-plain may act as a reservoir as it accumulates surface runoff much faster than the channel is able to discharge volume through its relatively small a nd restricted outlet. Hoggan (1997) notes that pronounc ed back-flow or a significant loop effect (discharge becomes a factor in water surface elevation) can aversely impact results generated by the Hydraulic Engineering Centers (HEC) computer program. COMPUTER PROGRAMS Floodwater level predictions were gene rated using the Hydrologic Engineering Centers River Analysis System 3.1 (HEC-RAS 3.1) computer program developed for the United States Army Corps of Engineers. Th e goal of the Hydrologic engineering Center (HEC) is to support the Unite d Sates water resources management activities. The Hydrologic Engineering Center is an organization within the Institute for Water Resources. It is the designated Center of E xpertise for the US Army Corps of Engineers in the technical areas of surface and groundwater hydrology, river hydraulics and sediment transport, hydrologic statistics and risk analysis, reservoir system analysis, planning analysis, and real-time water c ontrol management(HEC 2003). Programs are developed for the Army Corps of Engineers but are available to the public and may be freely downloaded from the http://www.hec.usace.army.mil/default.html web site. The HEC-RAS 3.1 program is improved over HEC-RAS 2.0 in that it is able to compute unsteady flows, and it allows the user to in teract with the program through a graphical

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64 user interface (GUI). The program provides storage and data management as well as graphic capabilities (HEC 2003). Niemeyer (2002) mentions that Magilligan and Stamp used the HEC program to compare runoff, over time, within a Georgia dr ainage basin. Gergel et al, (2002) used the HEC program to study the effects of lev ee removal on the Wiscons in River. HEC has been developing computer programs for hydrol ogic engineering and planning analysis procedures since its inception in 1964. HECRAS has been used as standard modeling software in the estimation of flood stage a nd extent in hundreds of hydrological studies (HEC 2003). A series of basin cross-s ections represent floodplain topography and Manning Numbers provide roughness coefficients. An algorithm solves a one dimensional energy equation between the cr oss-sections. Water surface profiles are computed from one cross section to the ne xt by solving the Energy equation with an iterative procedure called the sta ndard step method (Brunner 2002). The Hydrologic Engineering Companys River Analysis System (HEC-RAS) incorporates two methods by which flood levels can be estimated. The user must choose either Steady Flow or Unsteady Flow regimes. Steady Flow was chosen for this study primarily due to the minimal slope of the ba sin bottom. The Steady Flow regime is designed for application in flood-plain management and flood insurance studies to evaluate floodway encroachments. This co mponent of the modeling system is intended for calculating water surface profiles for steady gradually varied flow. The system can handle a single river reach or a full networ k of channels. The accuracy of the model depends upon the accurate input of Geometric Data, Boundary Conditions, and the

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limitations of the Solution Scheme. The output must be checked by the operator to insure that reasonable results are produced by the system (Brunner 2002). COMPUTATION PROCEDURE Water surface elevations are determined at each cross-section by an iterative solution of the Energy equation and the Energy Head Loss equation as described below. Computations begin downstream and proceed upstream. Downstream surface elevations are usually not known and must be assumed. 1. For a subcritical profile choose a known or assumed water surface elevation upstream. Subcritical is defined as a water surface elevation above the hydrologic critical level. Critical level is that water surface elevation where in the energy head is minimal (Brunner 2002). 2. Based on #1 determine the total conveyance and velocity head. 3. From #2 compute S and solve the Energy Head Loss equation. 4. From #2 and #3 solve the Energy equation for the water surface (WS). 5. Compare the value of WS with the value assumed in step #1; repeat steps 1 5 until the values agree to within .01 feet of the upstream elevation (Brunner 2002). The equation for Expansion and Contraction losses is: gVagVaChce22~]1[222211 65

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Where: C = the contraction or expansion coefficient (Brunner 2002). Which is used in the Energy equation. The Energy equation is: ehVaZY V aZYgg22~]2[2211112222 Where Y = Depth of water at cross sections Z = Elevation of the main channel invert V = Average velocities a = velocity weighting coefficients g = gravitational acceleration h = energy head loss (Brunner 2002). 66

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The Energy Head Loss equation is: ggVaVaCLShfe22~]3[221122 Where: L = Discharge weighted reach length S = Friction slope between two sections C = expansion or contraction loss coefficient (Brunner 2002). PMF magnitudes will be generated using the National Flood Frequency Program (NFF) (USGS Water-Resources Investigations Report 02-4168). The HEC-RAS program is based on five assumed factors. The flow varies gradually. The flow is one-dimensional but is corrected for horizontal velocity changes. The channel slope is relatively small. The average friction slope between cross-sections is constant. The boundary conditions are static (Hoggan 1997). 67

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68 There are five steps in the development of a hydraulic rive r study using HEC-RAS 3.1. The first step is the creation of a project file. Next, the river network is defined and geometric data such as basin cross-secti ons, river and reach de lineations are created. Flow and boundary conditions are then input prior to developing the analyses and reviewing the results (Hoggan 1997). In order to facilitate these five steps HEC-RAS operates in conjunction with the Hydrologi c Engineering Centers Geographic River Analysis System (HEC-GeoRAS), a comp anion program also developed by the Hydrologic Engineering Center for the US Army and an extension to the ArcView 3.3 Geographic Information System (GIS). H ec-GeoRAS enables the development of an import file that consists of user create d and named rivers and reachs with station identifiers, cross-sections of the draina ge basin with roughness coefficients, levee alignment, elevation and location, along with ineffective flow areas and storage areas. After this file is generated and imported in to HEC-RAS, hydraulic structure information such as culvert size and type with Ma nning numbers, channel slope, beginning and ending surface elevations, or flood hydrographs, may be input prior to processing that produces water surface and velocity data. This output file may then be used in ArcView GIS for further analysis (Ackerman 2002). It is within the ArcView program that flood inundation mapping takes place. A Triangulated Irregular Network (TIN), generated from the two foot contour data, was overlaid with the flood inundation depiction generated in HEC-RAS. One-meter aerial photographs from the Hillsborough Tax Assessors office were layered such that the existing streets and subdivisions are visible. Lakes and bank-full channel boundaries have also been layered to enable the reader to easily discern the extent of flooding. Maps

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69 were created such that flooding depth is evident. All data related to a particular analysis is accessed from a series of files recognized by file extensions that are native to HECRAS and HEC-GeoRAS. These files consist of Project Files (.PJR), Plan Files (.P01to .P99), Run Files for each plan (.001 to .099) Geometric Data Sets (.G01 to .G99) and Steady-flow or Unsteady-flow Data Sets (.F01 to .F99). HEC-GeoRAS provides a mouse operated drawing object that allows the river network to be created on top of a contour ma p of the drainage basin. Each river and river-reach is named at this time. A drawing object is also provided that allows basin cross-sections to be drawn. These cross-sect ions must cross the river centerline at near right angles and must extend to elevati ons higher than the maximum flood elevation. Cross-sections must also be close enough together to indicate geographic features such as connecting drainage canals or d itches. Structures such as bridges, culverts, weirs and other hydraulic features are then added and stored in the Geom etric Data File. Profiles, discharge values and boundary conditions are entered and stored in the Flow-Data File (Hoggan 1997). OPERATIONAL PROCEDURE Data related to surface contours were then formed into a triangulated irregular network (TIN) and were imported into a Geographic Information System (GIS). An extension to the GIS ArcView; the Hydrol ogic Engineering Centers Geographic River Analysis System (HEC-RAS) was then used to develop a geospatial data file. HEC-RAS is a two-part program composed of HE C-GeoRAS for preprocessing and HEC-RAS, which develops water surface elevations and flow rates. The pre-processing area of the

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70 program (HEC-GeoRAS ) uses a digital el evation model (DEM) in the form of a Triangulated Irregular Network (TIN) to pr oduce an import data file describing and naming rivers, and reaches, with station iden tifiers and cross-sectional bank stations. Reach lengths for stream centerline and right and left riverbank limitations are delineated at this time. Manning roughness coefficients can also be introduced into the import file. The extension allows the input of the alignment and location of levees, ineffective flow areas, and storage areas. The import file pr oduced by the pre-processing feature of HECGeoRAS is then loaded into the HEC-RAS program. Hydraulic boundaries are input into th e HEC-RAS program at cross-sections locating the beginning and end of each reach an d at any point where a flow change would be expected. HEC-RAS then produces water su rface profile and velocity data sets in an output file used by the post-processing sect ion of HEC-GeoRAS. The water surface profile data is used within ArcView GIS to develop a water surface TIN, and the intersection of the water surface TIN with the terrain model TIN provides flood visualization. The results can be projected in two-dimensional or three-dimensional views. These data can then be uti lized in map production (Ackerman 2002). Flood hydrographs and PMF magnitudes used in the HEC program were generated using the National Flood Frequenc y Program (NFF). USGS Water-Resources Investigations Report 02-4168 inco rporates this computer program that allows the user to input drainage basin size, slope, and lag time (See figure 22,23). These inputs are then used within the program to estimate the magnitude and frequency of floods for ungauged sites within the United States or its possession s. The return frequency of these estimated floods ranges from two-year to five hundred-y ear return periods. Estimates of 100to

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71 500-year flood discharges are used by th e Federal Emergency Management Agency (FEMA), and National Park Service in defining floodplains. Floodpl ain boundaries based on the 500-year flood are used mostly for planning purposes to identify areas that would be inundated by an extreme flood. The various De partments of Transportation at the State level have begun to evaluate the risk of th eir bridges being subjected to scour damage during floods on the order of 100to 500-year or greater return periods (USGS 2002). The National Flood Frequency (NFF) program will also provide the Crippen and Bue (1977) envelope curve values for seventeen regions within the conterminous United States, including region three. Region three contains basins that are comparable in hydrological and meteorological characteristics and also in size to the study area. Very large floods or Probable Maximum Floods (PMF) are estimated in several ways, but the most common are either floods based on the maximum flood experienced on a similarly sized basin located in the same region, or floods based on the Probable Maximum Precipitation (PMP). The extreme flood used in this study is based on the maximum observed flood for a given size watershed. These da ta are taken from flood-enve lope curves developed by Crippen and Bue (1977) and Cr ippen (1982). The curves were developed by plotting the maximum known flood discharges for a given drainage area in seventeen flood regions of the conterminous United States. The flood-e nvelope curves appr oximate the maximum flood-peak discharge that has been regiona lly experienced for a given size watershed. These values do not have probability of ex ceedance due to their extreme nature (USGS 2002). These extreme flood values will be used in the estimation of area inundated within the Selfer (Baker Canal) drainage basin.

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72 The Hydraulic Engineering Center (HEC ) program was run in Steady Flow mode and the Canal was considered an open channel. At Probable Maximum Flood magnitudes all road crossings will be submerged and the roadways will act as smoothtopped weirs. Roughness coefficients were adju sted for submerged drainage structures.

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73 CHAPTER FIVE RESULTS The Hillsborough County Engineering Depa rtment has completed an extensive hydrologic study of this general area in an at tempt to develop a comprehensive mitigation plan that will accommodate a 25-year flood event. This study which used the EPA Stormwater Management Model (SWMM) modified by the County staff, (model HCSWMM4.31B) also defines the Countys esti mate of the 100-year flood extent. The relatively short historic length of hydrologic data usually limits fl ood studies to the 100year flood. The County estimate is the most current and localized flood information available. The estimates of floods up to the level of the 100year flood, in this paper, were compared to the Hillsborough County 100-year flood. It is noted that the estimate of flooding extent as calculated by Hillsborough County is based on the predicted 100 year rainfall event which is eleven and one-half inches (11.5in.) of rainfall in a twenty-four hour period (See figur e 20) (NOAA 2003c). INPUT DATA for CALCULATIONS Flood estimates of events of greater retu rn periods than 100 y ears do not generally have historic local data with which they can be compared. The 500-year flood is the largest flood that is used fo r planning, management, and de sign. This flood discharge has

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Fig 20 These contour lines indicate the 1% per year maximum rainfall that can be expected in the United States. 74 a 0.2 percent chance of being exceeded in any given year. The 500-year flood is the most extreme flood discharge usually used in the flood-frequency programs of the US Geological Survey and of the US Army Corps of Engineers (USGS 2002). Floods that are expected to occur in excess of 100 year return periods are seldom estimated by regression equations due to short historical records of flooding (Bridges 1982). For this reason flood magnitudes and hydrographs for return periods exceeding 100 years will be calculated from Crippen and Bue (1977) envelope curves. These data are available through the USGS National Flood Frequency Program (See figure 21).

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Results Window from National Flood Frequency Program (NFF) Fig.21 Information input into the upper panel results in peak flows for recurrence intervals. Note the flows for 100yr, 500yr, and Maximum flood flow. The parameters in the upper panel of figure 21 are produced by the input in the window as shown in figure 22. 75

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Input Window for National Flood Frequency Program (NFF) Fig. 22 Preliminary data are input into this Window of the NFF program that then generates flood flow rates. The 100-year, 500-year and the Probable Maximum flood flows are of particular interest in relation to this study. As can be seen from figure 21 these flows are 1240cfs, 1950cfs, and 41,900cfs respectively. These data were supplied to the HEC-GeoRAS program in order to generate an initial input file. This file consists of designated names for the River, names, lengths and stationing for each reach of the River, and cross-sections at relevant points along the various reaches, all of which are integrated with a Triangulated Irregular Network (TIN) that supplies elevation data for the calculations. Figure 23 illustrates the preRAS portion of HEC-GeoRAS, which prompts for the creation of the River centerline, the left and right river banks, flow-paths, and cross-section lines. When these features have been correctly created, the program will assign reach lengths, stationing, three dimensional centerline elevations, and three dimensional 76

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cross-section elevations. The Import File is then created, which can be used in the HEC River Analysis System. Prompt Window for HEC Program Fig. 23 The program creates the Information listed by each line in the Prompt Window. The result is the Geographic Input File. When the import file is imported into HEC-RAS, a geometric data file is created as seen in figure 24. This file generates a depiction of cross-sections that are stationed along the river reaches with the stationing beginning at the lowest elevations and proceeding upstream (North to South) and three shorter tributaries in a West to East orientation. The outfall of the study area is at station 16,943.87. Data downstream 77

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(North) of this station is necessary so that the program will have enough information to minimize any error induced by the estimation of projected flows. Diagram of Geometric Import Data File Fig 24 This Input File is the basis upon which all calculations are Processed. The Green lines represent cross-section lines where elevations from the topography via a Triangulated Irregular Network are obtained. The program uses the difference in elevation between cross-sections to calculate energy losses and ultimately flood surface extent. 78

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Steady Flow data input into the HEC program Fig 25 The flow data for each of the river and tributary reaches for the 100yr (PF1), 500yr (PF2) and PMF (PF3) must be correctly input into the HEC flood program prior to any surface calculations. It is possible to calculate numerous flood profiles, or scenarios using the same geographic input file. In this instance, three profiles PF 1, PF 2 and PF 3 represent an estimate of the 100yr, 500yr, and Probable Maximum Flood respectively. Note the values of 1240, 1950 and 41,900cfs on line four of figure 25. These are the flow rates from the USGS National Flood Frequency Program for a basin of this size and slope in Crippen and Bues physiographic area number three. These data along with the required boundary data shown in figure 26 produce the inundation maps shown in figures 27,28. 79

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Boundary Conditions (limits) Fig 26 Boundary data is obtained from the two foot contour data set and is Used in conjunction with the input flow data by the HEC program. WS = water surface elevations. Upstream boundaries are established from ground elevations while downstream elevations are estimates used by the flood program to enable initial computations. 80

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81 CHAPTER SIX DISCUSSION In discussing the research question: Is the easily acquired and inexpensive flood program, Hydraulic Engineering Centers River Analysis Sy stem (HEC-RAS), a viable solution to flood inundation on a small draina ge basin? A comparison of the HEC estimate with Hillsborough Countys estimate is examined below. The Hillsborough County Stormwater Division of the County Engineering Department has completed a comprehensive stud y of five major basins within the County boundaries. Total cost of this comprehensive study was approximately twelve million dollars. The Baker Canal (Selfer) basin was in cluded in the study. The basic goal of the County investigation was to determine the nece ssary steps needed to mitigate a twentyfive year event such that a minimum number of structures and county roads would be affected. In the pursuit of these goals an es timate was made of the extent of the 100yr flood within the specific study area of this thesis. The flood inundation map shown in figure 27 is a graphic depiction of the HEC 100 year flood estimate (green) superimposed over the 100 year flood as estimated by the Hillsborough County Engineering Department, Storm Water Divisi on (purple). With the ex ception of several separated areas to the East, the HEC estimate differs less than 1.5% in area from the Hillsborough County prediction. These Eastern areas resu lt from the high rate of precipitation, 11.5 inches in a 24hr. period, used in the Hillsborough County Storm Water Management

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82 Model (SWMM) and the inherent differen ces in design goals of the HEC and SWMM programs. The HEC program leans primarily to ward river analysis and uses recorded or estimated flow rates as its primary in put. The SWMM program is a stormwater management tool that uses precipitation am ounts as a basis for peak flow rates. These shallow surface areas in the Eastern area of the basin canno t be duplicated in the HEC model, running in Steady Flow Mode, regard less of the flow numbers used in the tributaries from these areas. (See figure 25, ro w 7,16) Relief along the basin center is in the range of 1 to 1.5ft. per m ile, while relief from the centerline toward the East in approximately 30ft. per mile. The HEC program routes surface water in this area downslope into the channel area. The SWMM program tends to indicate short-term storage. For the purpose of flood estimation of areas that may exhibit shallow flooding the SWMM model appears to be superior. Th e HEC program has produced a comparable estimate of channel flooding in a very s hort time with a minimum of financial expenditure.

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HEC 100yr Flood Estimate overHillsborough County 100yr FloodEstimate Se p arated areas Scale 1in = 2 miles Fig. 27 Except for the separate areas to the East the Hillsborough estimate is virtually hidden by the HEC flood estimate. For comparison figure 28 is the reverse of figure 27, showing the Hillsborough 100yr flood superimposed over the HEC 100yr flood. 83

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Hillsborough County 100yr Flood EstimateOver HEC 100yr Flood Estimate Scale: 1in = 2 miles Fig. 28 In this map the HEC 100yr flood estimate is virtually hidden behind the Hillsborough County 100yr flood estimate. 84

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Numerous iterations of the input process in the HEC program in Steady Flow Mode result in similar results as seen above. When properly entered into the HEC program the target flow rate of 1240cfs for the 100yr flood results in very close agreement with the Hillsborough County estimates. Below in figure 29, the FEMA estimate of areas at risk of flooding are displayed for comparison with the HEC and Hillsborough estimates. Note the similarities, and the areas to the East of the main channel in the Hillsborough estimate that are nearly absent in the FEMA and HEC estimates. Comparison of Three 100yr Flood Estimates Study Area FEMA Hillsborough Fig. 29 Note the minimal size of the separated areas to the East of the main channel in the Study Area and FEMA flood estimates compared to the Hillsborough estimate. 85

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86 Having established the relevance of th e HEC model, to the study basin, by comparing the 100yr flood area generated by both the SWMM and HEC models and finding them in agreement within reasonable tolerance, it is now possible to proceed with estimates of flood levels at extended return pe riods. It is recognized that the 100yr flood is of a much smaller magnitude than the PMF flood to which this study aspires but the 100yr flood is the best and most recent flood estimate available with which the model can be compared. FLOOD AREA In discussing the research question: What is the area of th e study basin that will be inundated by a Probable Maximum Flood? Estimated flood areas are examined on the following pages. Figure 30 indicate s that there is little differe nce in surface area between the HEC, Steady Flow 100yr flood over the HEC 500yr flood. For comparison figure 31 shows the reverse of figure 30. There is a flow rate difference of 710cfs. Figures 32 and 33 are of interest in that they indicate a difference of 0.06ft in maximum flood depth at Muck Pond Rd. (outfall). Table 5 (pg. 106) indi cates only a 0.02ft. increase in surface elevation between the 100yr, a nd 500yr. flood levels Velocities are very low at 0.02 to 0.03fps. The 100yr flood is estimated to exte nd 6,527ft. in width while the 500yr flood is only slightly larger at 6,534ft wide. This tabl e also indicates that the flood meets program requirements that state that th e flow be steady and slowly varied (Brunner 2002) (See table 5).

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HEC 100yr Flood Estimate overHEC 500yr Flood Estimate Scale: 1inch = 2 miles Fig. 30 Comparing the HEC 100yr and 500yr flood estimate results in very little apparent difference. 87

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Scale: 1inch = 2 miles Fig. 31 The reverse of figure 30 also indicates very little apparent Difference between the HEC 500yr and HEC 100yr flood estimate. 88

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Scale: 1 inch = 0.5 miles Fig. 32 In this enlarged view of 100ft flood depths note the maximum depth at the intersection of Muck Pond Rd. and the Baker Canal (basin outlet). 89

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Scale: 1 inch = 0.5 miles Fig. 33 In this enlarged view of 500ft flood depths note the maximum depth at the intersection of Muck Pond Rd. and the Baker Canal (basin outlet). 90

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The USGS National Flood Frequency Program (NFF) indicates that the Probable Maximum Flood Flow for this basin, in this physiographic area (region 3 Crippen and Bue) is 41,900cfs. The input flow rates for this profile (PF-3) are listed in figure 25. A map showing the estimated area of inundation resulting from this maximum flood is shown in figure 34. Scale: 1 inch = 2 miles Fig 34 This map illustrates the major goal of the study. 91

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92 The Probable Maximum Flood area c overs 3,146 of the 13,251 acres that comprise the study area or 23.7% of the study area basin. Under normal conditions only 4.3% of the basin area is occupied by lakes or steams. This estimate of the extent of a Probable Maximum Flood indicates that the flood will affect a number of homes and structures. Figures 35 to 40 illustrate the ex tent of the estimated flood in relation to recent aerial photographs. EXAMPLE ANALYSIS In discussing the research question: What is the significance of the Probable Maximum Flood on the study area? Maps are displayed that demonstrate some analysis possibilities. Even though most of the land area in the vicin ity of the study area outfall (Fig 38) is agricu ltural, the flood extent estimate indicates that approximately 207 buildings will be inundated. In all cases a fi eld survey will be necessary in order to determine an exact number of structures that may be affected. North of Muck Pond Rd and outside the study area lies the Pemberton Creek subdivision; an additional 70 to 80 buildings in this subdivision appear in the inundated area. This subdivision has experienced flooding, that was estimated by Hi llsborough County to be at the 50yr level, in 1997. A large shallow ephemeral lake dominates the estimated PMF flood zone South of State Highway 92. This lake is the treeless ar ea in the center of fi gure 36; there are no structures within this dry lakebed. Rainfa lls of two inches per twenty-four hour period will result in flooding of parts or all of th is ephemeral lake depending on existing ground

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water levels. Approximately 98 structures will be affected by the estimated PMF in the area depicted in figure 36. The majority of these structures are in an area surrounding the PMF at Muck Pond Rd. (outfall) Pemberton Creek Sub. Fig. 35 The Probable Maximum Flood area at the basin outfall (Muck Pond Rd). 93

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small-unnamed lake in the center left of the figure. See figure 37 for an enlarged map of this area. Fig. 36 Note the large ephemeral lake in upper center of the figure and the small Lake in the upper left central area of the figure. The majority of the structures in this figure surround this small-unnamed lake. 94

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Fig. 37 In this enlarged map of the small unnamed lake the development surrounding the lake is apparent. 95

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Fig. 38 Lake Hooker is the dark area to the left of the lower central portion of the figure and Lake Weeks is in the upper left area of the figure. The majority of the structures in this area are located near the bottom of the figure South of Lake Hooker. Approximately 245 structures are within the estimated PMF flood zone in this figure. One hundred and seventy-four buildings out of the two hundred and forty-eight 96

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structures that compose the Lake Shore Ranch subdivision (bottom left) are within the estimated PMF flood zone. See figure 39 for and enlarged map of this flood area. PMF at the Lake Shore Ranch Subdivision Fig. 39 This is an enlarged area of the Lake Shore Ranch Subdivision indicating the estimated Probable Maximum Flood boundary as it cuts across the development. 97

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Fig. 40 Figure 40 illustrates the Probable Maximum Flood area in the vicinity of Lake Valrico and Long Pond. Lake Valrico is situated in the bottom center of figure 40, while Long Pond is left of center in the upper portion of the figure. Approximately 526 structures are within the estimated PMF zone in figure 40. The number of inundated structures is derived from counts of structures visible in the overlaid aerial photographs. A field survey would be necessary to determine the actual number of structures that exist inside the estimated PMF zone. An enlarged map of the area appears in figure 41. 98

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PMF Area Lake Valrico, Long Pond Fig. 41 Developed area around Lake Valrico (South) and Long Pond (North). The dredged canal between the lakes is visible as a tan colored and dog-legged line. The following are several filled cross-sections from the model computations, beginning at the outfall and proceeding up stream (See figures 42 to 47). 99

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Study area Outfall at Muck Pond Rd. Fig. 42 Cross-section at river station 16943.87 (Basin Outfall). Figure 42 indicates several separate conveyance areas East of the main channel. These areas have hydraulic connections to the main channel as indicated in figure 34. The conveyance areas appear to be separated due to the routing of the cross-section for this river station. The cross-section does not cross the channel in a straight line but is dog-legged (see figure 24) so as to include pertinent topography as is indicated in figure 42. These cross-sections are exaggerated at a ratio of 50 to 1 in order that the vertical relief along the cross-section can be easily discerned at this scale. Cross-sections are aligned such that important relief will be included in the program calculations and they must span the channel area from elevations higher than the maximum water surface. Cross-sections 100

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must also be close enough together such that the hydraulic head between them is evident at the shallow relief exhibited by the main channel. Ephemeral lake South of State Highway 92 Fig. 43 Cross-section at river station 23648.18 (South of Hwy. 92). Lake Weeks 101 Fig. 44 Cross-section at river station 35035.09 (Lake Weeks).

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Area between Long Pond and Lake Hooker Fig. 45 Cross-section at river station 38655.71 (High Point between Long Pond and Lake Hooker). Lake Valrico Fig. 46 Cross-section at river station 43112.09 (Lake Valrico). 102

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Head-waters of the Study Area Fig. 47 Cross-section at river station 48061.46 (Basin head-waters). These cross-sections illustrate the estimated Probable Maximum Flood level at each location. Profiles have also been generated that graphically illustrate the estimated Probable Maximum Flood levels along the flow-line of the Canal as well as at each overbank location. For clarity the overbanks are not visible (See figure 48). 103

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Profile Baker Canal Fig. 48 River station 16943.87 is the outfall (top of road embankment) at Muck Pond Rd. River station 38655.71 is the high point between Long Pond and Lake Hooker. The profile indicates a relatively rapid change in elevation between the high point and the next downstream cross-section. This is still within the Hydraulic Engineering Centers River Analysis (HEC-RAS) program parameter due to the minimal flow rate for the basin as a whole and minimal volume in this area (See Figure 45). Figure 49 illustrates the flow-line profile of Tributary 1. This tributary enters Lake Valrico from the East. 104

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Profile Tributary 1 Fig. 49 The Tributarys Probable Maximum Flood surface is indicated by the dashed red line. Note that the maximum depth of the Tributary is just over 3ft. The tributary appears relatively deep at its outfall due to the junction point location, which is a considerable distance from the lake shoreline toward the center of the lake. A graph depicting the width of the top of the estimated Probable Maximum Flood area along the alignment of each cross-section is shown in figure 50. 105

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Top width of Probable Maximum Flood Channel Lengt h Fig. 50 The arrow indicates the outfall location. Note the widening of the flood area just down-stream of this point. Figure 51 illustrates the velocities at each cross-section. The velocity is uniformly low for the main channel. This meets the requirements of the Hydraulic Engineering Centers River Analysis (HEC-RAS) program parameters that call for a steady and slowly varied flow (Brunner 2002). 106

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Probable Maximum Flood Velocities at Main Channel High point betweenLong Pond and LakeHooker Basin outfall atMuck Pond Rd. Fig. 51 Note the relatively high velocity between Long Pond and Lake Hooker. The volume at this point is minimal (See figure 45). Table 5 enumerates Total Calculated Flow, Minum Channel Elevation, Flood Surface Elevation, Channel Slope, Velocity in the Channel, Flow-Area, and Top Flow Width for each of the profiles 100yr (PF 1) 500yr (PF 2)and Probable Maximum Flood (PF 3) at each cross-section location. 107

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Table 5 PF 1Pf 2Pf 3PF 1Pf 2Pf 3PF 1Pf 2Pf 3PF 1Pf 2Pf 3PF 1Pf 2Pf 3PF 1Pf 2Pf 3PF 1Pf 2Pf 3PF 1Pf 2Pf 3 Model Summary Output Table continued on next page 108

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Table 5 continued from previous page PF 1Pf 2Pf 3PF 1Pf 2Pf 3PF 1Pf 2Pf 3PF 1Pf 2Pf 3PF 1Pf 2Pf 3 Table 5 Model Summary Output Table PF 1, PF 2, and PF 3, are the flood profiles for the 100yr, 500yr, and Probable Maximum Flood respectively. Maximum model flow for each of these profiles is at river station 16943.87. 109

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110 CHAPTER SEVEN CONCLUSION The primary goals of the study were to model a Probable Maximum Flood in the study area and map the inundated area. This was accomplished but it must be emphasized that this inundated area is an estimate and as such is subject to many variables over which there are little or no control. The size of a Probable Maximum Flood, as calculated by Crippen and Bue 1997, is itself an estimate in which there is considerable variability. There is also very little history related to this type of study and most importantly a Probable Maximum Fl ood has not occurred, within the study area, with which the estimate can be compared. Until such time as confirming data is available this estimate must be viewed as being consid erably larger or smaller in area than an actual event. By definition confidence limits cannot be placed on the magnitude of a Probable Maximum Flood, thus it is not possible to estimate a plus or minus percentage error for the inundated area. Th e study can be considered to be, in theory, practically adequate only when an actual event occurs and an investigation of that event can be compared to this study and the resu lts indicate reasonable agreement.

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111 GENERAL PROCEDURE The general procedure that was followed in the production of this study model was as follows. 1. It was realized that a ve ry large inland flood was possible in the local area. 2. Information as to the extent of ma ximum flood inundation was not available. 3. The study area basin had been extensively investigated for flooding of a less severe event. 4. Computer software was av ailable that would allow an estimate of a Probable Maximum Flood. 5. Suitable data was available. 6. Computer programs and data were collected. 7. The basin was modeled and an esti mate of inundation established. FLOOD IMPACT The model estimates that the average fall pe r foot in the main channel is slightly over .0003 foot per foot or approximately 1.53ft per mile. This resulted in low flow velocities averaging 1.8fps (See table 5). Thes e low flow velocities will result in much of the affected area remaining in a flooded stat e for considerable lengths of time. Damage rises in proportion to the lengt h of time structures are submerged. Thus while the flood flow may not move well built structures off of their foundations, th e extended period of submergence could be expected to raise damage estimates. Early in the study there was some concern th at the basin flood-plain might act as a reservoir as it accumulated su rface runoff faster than the ch annel is able to discharge

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112 volume due to the minimal channel slope. Th ere was also a possibi lity that pronounced back-flow (discharge becomes a factor in wa ter surface elevation) mi ght aversely impact results generated by the Hydraulic Engineer ing Centers (HEC) computer program. The basin does indeed seem to act as a reservoir as is seen in the very slow flow velocities listed in table 5. There is however no evidence of back-flow in significant amounts as table 5 and figure 48 indicate a small but c ontinuous fall in the PMF flood surface. The length of the Main Channel centerline is 43,729ft or 8.3miles. The length of Tributary 1s centerline is 20,251ft or 3.8miles. The Study Area covers 13,251 acres while the modeled area including the area Nort h of the outfall necessary for program calculation includes 18,787.4 acres. Table 6 compares the Hillsborough and HEC estimates of flood area to the total area in cluding area added the North for calculation purposes. This estimate of a Probable Ma ximum Flood (PMF) indicates that 3,146 acres (23.7%) of the 13,251 acres that compri se the study area will be inundated. Table 6 Hills 100yr Flood HEC 100yr Flood HEC 500yr Flood HEC PMF Total in Model Area in Acres 3,208.9 3,431.6 3,491.4 4,524.6 18,787.4 % of Total 17 18.3 18.5 24.1 % Larger than Hills 100yr Flood 0 1.3 1.5 7.1 Comparison of Flood Areas in calcul ations to Total Area calculated.

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113 A count of the structures that are visi ble in recent aerial photographs of the estimated extent of Probable Maximum Flood z one indicates that the flood will affect one thousand and seventy six (1,076) home s and other structures. The Hillsborough County Planning Commission is predicting that much of the open or agricultural land (41% of the total land area with in the Study Area) will be developed into residential and light industrial or comme rcial use (Hillsborough 2002). Eighty-five percent of estimated Probable Maximum Flood area is li sted, as currently developed, open, or agricultural land (See figur e 52). Table 7 enumerates the areas of existing and proposed land development in the PMF zone. Table 7 Existing Development Proposed Development Existing Water Development Not Proposed Total in Study Area Acres 670 863 1133 480 3146 % of Total 21.3 27.4 36.0 15.3 100 Landuse Within the Study Area.

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Landuse Within the PMF Flood Zone Fig. 52 This map provides a visual impression of the landuse within the Probable Maximum Flood area. Eight hundred and sixty three (863) acres or 27% of the land within the PMF flood zone is listed for future development. A considerable area within the PMF flood 114

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115 zone is already occupied by residential and commercial development. Six hundred and seventy (670) acres or 21% of the PMF zone is currently listed as residential or commercial development. Under normal weather conditions existing lakes, ponds, reservoirs, and canals submerge one thousa nd one hundred and thirty three (1,133) acres or 36% of the PMF zone. Only 15% of the useable land area within the PMF zone is not currently either developed or listed for deve lopment (See table 7). The majority of this 15% is mixed hardwood coniferous forest. The implication of this prediction of increased floodplain use by a governmental development agency is of considerable interest. This tendency fo r government not only to allow but encourage development is area s of possible catastrophi c flood is a driving force behind increased disaster losses. On the surface, development of this floodplain can be justified in that the Probable Maxi mum Flood, if it ever occurs, will likely occur some time in the distant future. In the meantime the County will enjoy the taxes generated by development and the population of the floodplain will enjoy the use of the land. When the flood does occur increased losses will accrue due to the higher concentration of structures and infrastr ucture necessary to serve the floodplain population. If mitigation is to be effective it must be in pla ce prior to the event. Land prices are less prior to development; thus it would seem reasonable to acquire land for parks or other public use in possible floodplain areas prior to development. This type of action would be true mitigation, it would o ccur prior to the flood event and minimize damage when the event occurs. It would s eem that the lesson related to pre-planed mitigation rather than reconstruction has not been fully understood or implemented.

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116 SUITABILITY OF METHODS USED This model is dependent upon several assumed data sets. The accuracy of these data directly affects the accuracy of the m odel output. Nevertheless the model may have considerable worth as a predictor of maximum flood extent in many areas. This type of study may be appropriate in ar eas such as West Central Florida. This area is populated with numerous shallow depressions that have not exhibited the tendency to retain substantial amounts of surface water for many years. These areas are drained by the Karst nature of the soil and underlying st rata. In times of exceptional precipitation amounts these dry lakebeds will become holding areas for large amounts of surface water. Due to the extended period in which these areas have remained dry and due to the increasing population from afar, few people either in the general population or in decision-making positions can recall events that lead to flooding in these depressions. In the ensuing years many of these areas have been subdivided for residential housing or business development. It is not expected that these developed areas would be abandoned if the potential for flooding were known but individual homebuyers and commercial builders may find this type of information usef ul when choosing areas in which to locate. The study was inexpensive in that the NFF and the HEC program are in the Public Domain and thus available at no co st to users. Data is likewis e often available at little or no cost, from local governmental agencies in many locations. The model can be applied to very small drainage basins. Crippe n and Bue Probable Maximum Flood envelope curves include basins as small as 0.2 square miles. This study focused on the area inundated by an estimated Probable Maximum Flood. However, in comparison to the C ounty study of the 100yr flood inundation area

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117 this study agreed within reasonable limits. As in any computation involving extrapolation from lower figures toward mu ch higher numbers there is considerable concern as to the applicability of the info rmation gained from such an exercise. The County studied five draina ge basins including the Self er (Baker Canal) basin. Total cost of these studies was approximately twelve million dollars or an average 2.4 million dollars for each basin study. The County study has yielded large amounts of information in addition to area inundated and was initiated in order to determine cost and feasibility of mitigation agai nst a twenty-five year event. This study and the County effort can be compared only on the basis of area inundated at the 100yr level and it must be reiterated that both of these studies at the 100yr level are estimates based on extrapolated data. Having noted the considerable limitations of this investigatio n it seems reasonable to say that the methodology has merit in that is available at relatively low cost and usable on normal business computers. If the limita tions are understood real -estate advisors as part of their service to pros pective residential or commercia l clients could undertake this type of study. FOLLOW UP STUDY The value of this investigation will be greatly enhanced if a major flood occurs within a time span such that the landuse and demographics of the basin have not appreciably changed. When a major flood ev ent does occur in the study area there is little doubt that several studies will be initiated. These studie s will then be available for

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comparison with this preemptive investigation and a serious evaluation of this type of flood study can be accomplished. If it is found that the pre-flood model and post-flood data agree within a reasonable range then the usefulness of pre-flood investigations will be enhanced. 118

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REFERENCES Ackerman, Cameron T. 2002 Hydraulic Engineering Centers Geographic River Analysis System Users Manual On line h ttp://www.hec.usace.army.mil/software/hec-r as/hecras arcinfo_download.htm Bridges, Wayne C. 1982. Technique for Estimating Magnitude and Frequency of Floods On Natural-Flow Streams in Florida U.S. Geological Survey Water-Resources Investigations 82-4012 Brunner, Gary W. 2002. HEC-RAS River Analysis System Hydraulic Reference Manual U.S. Army Corps of Engineers Census, U.S. 2003. On line http://eire.census.gov/popest /data/counties/tables/COEST2002/CO-EST2002-01-12.php Cohon, Jared L. (Chairman) Com mittee on Techniques for Estimating Probabilities of Extreme Floods. 1988. Estimating Probabilities of Extreme Floods: Methods and Recommended Research National Research Council Academy Pr ess: Washington D.C. Crippen, J. R. 1982. Envelope Curves for Extreme Flood Events Hydraulic Journal, American Society of Ci vil Engineers, Vol. 108, No. HY10, pp 1208-1212. Crippen, J.R., and Bue, C.D., 1977, Maximum Floodflows in the Conterminous United States: U.S. Geological Survey Water-Supply Paper 1887 Dunne, Thomas and Luna B. Leopold 1978. Water in Environmental Planning Freeman: New York Etheridge, Bob. 2001. Etheridge Announces Major Effort to Improve Inland Flood Forecasting, Develop Warning System for Inland Residents On line http://www.house.gov/etheridge /Press-InlandWarning.htm ESRI, 2003. Data and Maps CD-ROM, Redlands, CA. 119

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FEMA. 2003. Federal Emergency Management Agency Flood Insurance National Flood Insurance Program On line http://www.fema.gov/nfip/ask.shtm FEMA. nd. Flood Risk Map On line http://www.geographicnetwork.com Fenneman, N. M. 1931. Physiography of Western United States McGraw Hill: New York Fenneman, N. M. 1938. Physiography of Eastern United States McGraw Hill: New York Gergel, Sarah E. and Mark D. Dixon, Monica G. Turner. 2002 Ecological Applications. Ecological Society of America CA. HEC. 2003. Hydrologic Engineering Center. Who We Are Department of The Army Corps of Engineers Institute for Water Resources Hydrologic Engineering Center On line http://www.hec.usace.army.mil/default.html Hillsborough County Public Works Department Engineering Division, Stormwater Management Section. 2002. PEMBERTON CREEK/BAKER CANAL AREA: STORMWATER MANAGEMENT MASTER PLAN HCED: CD-ROM Hillsborough (b) County Public Works Department Information & Technology Services nd. GIS Geodata Directory On line http://maps.hillsboroughcounty.org/FTP_HTMLs/geodata_dir.html Hoggan, Daniel H. 1997. Computer-Assisted Floodplain Hydrology and Hydraulics McGraw-Hill: New York. Hoyt, William G. and Walter B. Langbein. Floods Princeton UP: New Jersey Jaeger, Stefan. 2002. Rhine Flood Hazard Mitigated With the Help of GIS ArcNews Vol. 24 No. 3 Johnston, R. J. 1997. Geography & Geographers: Anglo-American Human Geography since 1945 New York: Oxford UP. Lane, William L. nd. Paleohydrologic Data and Flood Frequency Estimation in Regional Flood Frequency Analysis Ed. V. P. Singh 1987. Reidel:Holland 120

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Lo, C. P. 2002. Concepts and Techniques of Geographic Information Systems Prentice Hall, NJ. Malhotra, Yogesh. 1994. On Science, Scientific Method and Evolution of Scientific Thought: A Philosophy Of Science Perspective of QuasiExperimentation. On line http://www.brint.com/papers/science.htm NCEP. 2003. National Center for Environmental Prediction On line http://www.nhc.noaa.gov/paststate.html Niemeyer, Kelly Anne, 2002. An analysis of the Impacts of Land Use Change and Greenspace on Runoff Rates in an Urbanized Watershed Unpublished Masters Thesis, University of Nebraska, Omaha NOAA. 2002. National Hurricane Center. Inland Flooding On line (http://www.nhc.noaa.gov/) NOAA. 2003a National Hurricane Center On line http://www.aoml.noaa.gov/general/lib/usahp.html NOAA. 2003b. National Hurricane Center On line http://hurricanes.noaa.gov/prepare/summary_hazards.htm NOAA. 2003c. RECORD MAXIMUM 24-HOUR PRECIPITATION BY STATE On line http://www1.ncdc.noaa.gov/pub/ data/special/max24hr.pdf NWS. 1997. National Weather Service U. S. Flood Deaths 1903-1997 On line http://www.essc.psu.edu/hazards/flood4.htm Ohio Department of Natural Resource s Division of Water Engineering Group. nd. Dam Safety: Probable Maximum Flood On line http://www.ohiodnr.com/water/pubs/fs_div/fctsht37.htm Peet, R. 1998. Modern Geographical Thought MA: Blackwell. Phillips, J.V., and H. W. Hjalmarson, H.W. 1996. Implication of TranslatoryWave Phenomena for Engineering Design On line http://az.water.usgs.gov/roughness/twave.html Pielke, Jr., Roger A., Mary W. Downt on, and J. Zoe Barnard Miller. 2002. Flood Damage in the United States 1926-2000 A Reanalysis of National Weather Service Estimates On line http://www.flooddamagedata.org/full_report.html 121

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Rappaport, Ed. 1999. Leading Causes of Tropical Storm Deaths in the U.S. 1970-1999 On line http://www.nhc.noaa.gov/HAW2/eng lish/surge/cyclone_deaths.gif Sepulveda, Nicasio, 2002, Simulation of Ground-Water Flow in the Intermediate and Floridan Aquifer Systems in Peninsular Florida Water-Resources Investigations Report 02-4009 Tobin, Graham A. and Burrell E. Montz. 1997. Natural Hazards Explanation and Integration. Guilford Press: New York Trochim, William M.K. 2000. Positivism & Post-Positivism On Line http://trochim.human.cornell.edu/kb/positvsm.htm UNESCO 2001. World Water Assessment Programme On line http://www.unesco.org/water/wwap/f acts_figures/managing_risks.shtml Unknown.a, 2003. Hurricane City On line http://www.hurricanecity.com/tampa.htm Unknown.b, 2003. Wunderground On line http://www.wunderground.com/hurricane/at192106.asp USGS. 2002. THE NATIONAL FLOOD FREQUE NCY PROGRAM, VERSION 3: A COMPUTER PROGRAM FOR ESTIMATING MAGNITUDE AND FREQUENCY OF FLOODS FOR UNGAGED SITES Water-Resources Investigations Report 02-416 Ward, Roy. 1978. Floods: A Geographical Perspective Wiley: New York 122