Airborne laser quantification of Florida shoreline and beach volume change caused by hurricanes

This dissertation combines three separate studies that measure coastal change using airborne laser data. The initial study develops a method for measuring subaerial and subaqueous volume change incrementally alongshore, and compares those measurements to shoreline change in order to quantify their relationship in Palm Beach County, Florida. A poor correlation (R2 = 0.39) was found between shoreline and volume change before the hurricane season in the northern section of Palm Beach County because of beach nourishment and inlet dynamics. However, a relatively high R2 value of 0.78 in the southern section of Palm Beach County was found due to little disturbance from tidal inlets and coastal engineering projects. The shoreline and volume change caused by the 2004 hurricane season was poorly correlated with R 2 values of 0.02 and 0.42 for the north and south sections, respectively. The second study uses airborne laser data to investigate if there is a significant relationship between shoreline migration before and after Hurricane Ivan near Panama City, Florida. In addition, the relationship between shoreline change and subaerial volume was quantified and a new method for quantifying subaqueous sediment change was developed. No significant spatial relationship was found between shoreline migration before and after the hurricane. Utilization of a single coefficient to represent all relationships between shoreline and subaerial volume change was found to be problematic due to the spatial variability in the linear relationship. Differences in bathymetric data show only a small portion of sediment was transported beyond the active zone and most sediment remained within the active zone despite the occurrence of a hurricane. The third study uses airborne laser bathymetry to measure the offshore limit of change, and compares that location with calculated depth of closures and subaqueous geomorphology. There appears to be strong geologic control of the depth of closure in Broward and Miami-Dade Counties. North of Hillsboro Inlet, hydrodynamics control the geomorphology which in turn indicates the location of the depth of closure.

Impacts of hurricanes on surface water flow within a wetland

Between 2001 and 2005, seven category 3 or higher major hurricanes made landfall within the US. The hydrologic impacts of these distinct climatic phenomena frequently occurring in wetland watersheds, however, are not well understood. The focus of this study was to evaluate the impacts of hurricane wind and rainfall conditions on water velocity and water elevations within the study wetland, the Florida Everglades. Specifically water velocity data was measured near two tree islands (Gumbo Limbo (GL) and Satin Leaf (SL)) and wind speed, water elevation, and rainfall were obtained from nearby wind observation stations. During the direct impacts of the hurricanes (Hurricanes Katrina and Wilma), water speed, flow direction, and hydraulic gradients were altered, and the extent of variation was positively related to wind characteristics, with significant alterations in flow direction at depth during Hurricane Wilma due to higher wind speeds. After the direct impacts, the longer lasting effect of hurricanes (time scale of a few days) resulted in altered flow speeds that changed by 50% or less. These longer lasting changes in flow speeds may be due to the redistribution of emergent vegetation.

Monitoring of Tree Island Conditions in the Southern Everglades: The Effects of Hurricanes and Hydrology on the Status and Population Dynamics of Sixteen Tropical Hardwood Hammock Tree Islands

In 2005 we began a multi-year intensive monitoring and assessment study of tropical hardwood hammocks within two distinct hydrologic regions in Everglades National Park, under funding from the CERP Monitoring and Assessment Program. In serving as an Annual Report for 2010, this document, reports in detail on the population dynamics and status of tropical hardwood hammocks in Shark Slough and adjacent marl prairies during a 4-year period between 2005 and 2009. 2005-09 was a period that saw a marked drawdown in marsh water levels (July 2006 - July 2008), and an active hurricane season in 2005 with two hurricanes, Hurricane Katrina and Wilma, making landfall over south Florida. Thus much of our focus here is on the responses of these forests to annual variation in marsh water level, and on recovery from disturbance. Most of the data are from 16 rectangular permanent plots of 225-625 m2 , with all trees mapped and tagged, and bi-annual sampling of the tree, sapling, shrub, and herb layer in a nested design. At each visit, canopy photos were taken and later analyzed for determination of interannual variation in leaf area index and canopy openness. Three of the plots were sampled at 2-month intervals, in order to gain a better idea of seasonal dynamics in litterfall and litter turnover. Changes in canopy structure were monitored through a vertical line intercept method.

Airborne Laser Quantification of Florida Shoreline and Beach Volume Change Caused by Hurricanes

This dissertation combines three separate studies that measure coastal change using airborne laser data. The initial study develops a method for measuring subaerial and subaqueous volume change incrementally alongshore, and compares those measurements to shoreline change in order to quantify their relationship in Palm Beach County, Florida. A poor correlation (R2 = 0.39) was found between shoreline and volume change before the hurricane season in the northern section of Palm Beach County because of beach nourishment and inlet dynamics. However, a relatively high R2 value of 0.78 in the southern section of Palm Beach County was found due to little disturbance from tidal inlets and coastal engineering projects. The shoreline and volume change caused by the 2004 hurricane season was poorly correlated with R2 values of 0.02 and 0.42 for the north and south sections, respectively. The second study uses airborne laser data to investigate if there is a significant relationship between shoreline migration before and after Hurricane Ivan near Panama City, Florida. In addition, the relationship between shoreline change and subaerial volume was quantified and a new method for quantifying subaqueous sediment change was developed. No significant spatial relationship was found between shoreline migration before and after the hurricane. Utilization of a single coefficient to represent all relationships between shoreline and subaerial volume change was found to be problematic due to the spatial variability in the linear relationship. Differences in bathymetric data show only a small portion of sediment was transported beyond the active zone and most sediment remained within the active zone despite the occurrence of a hurricane. The third study uses airborne laser bathymetry to measure the offshore limit of change, and compares that location with calculated depth of closures and subaqueous geomorphology. There appears to be strong geologic control of the depth of closure in Broward and Miami-Dade Counties. North of Hillsboro Inlet, hydrodynamics control the geomorphology which in turn indicates the location of the depth of closure.

Tree Islands in the Shark Slough Landscape: Interactions of Vegetation, Hydrology, and Soils

Executive Summary: This report presents what we have learned about tree islands of Shark Slough and adjacent marshes of Everglades National Park (ENP), based on ecological studies carried out in these wetlands during the period 2000-2003. The tree islands of Shark Slough share many features with tree islands elsewhere in the Everglades. Their current composition and community structure is determined to a large extent by recent hydrology, as well as by disturbances (fire, freezes, hurricanes, man). Tree islands have historical, cultural, and biological values that are recognized by nearly all parties to the Comprehensive Everglades Restoration Plan (CERP). Maintaining and/or restoring the health of tree islands are major objectives of CERP. Consequently, there is a need within CERP for tools to assess the health of tree islands, and to relate these measures to the hydrologic regime to which they are exposed.

Regional growth, structural change, and natural disaster

Hurricanes, earthquakes, floods, and other serious natural hazards have been attributed with causing changes in regional economic growth, income, employment, and wealth. Natural disasters are said to cause; (1) an acceleration of existing economic trends; (2) an expansion of employment and income, due to recovery operations (the so-called silver lining); and (3) an alteration in the structure of regional economic activity due to changes in "intra" and "inter" regional trading patterns, and technological change.^ Theoretical and stylized disaster simulations (Cochrane 1975; Haas, Cochrane, and Kates 1977; Petak et al. 1982; Ellson et al. 1983, 1984; Boisvert 1992; Brookshire and McKee 1992) point towards a wide scope of possible negative and long lasting impacts upon economic activity and structure. This work examines the consequences of Hurricane Andrew on Dade County's economy. Following the work of Ellson et al. (1984), Guimaraes et al. (1993), and West and Lenze (1993; 1994), a regional econometric forecasting model (DCEFM) using a framework of "with" and "without" the hurricane is constructed and utilized to assess Hurricane Andrew's impact on the structure and level of economic activity in Dade County, Florida.^ The results of the simulation exercises show that the direct economic impact associated with Hurricane Andrew on Dade County is of short duration, and of isolated sectoral impact, with impact generally limited to construction, TCP (transportation, communications, and public utilities), and agricultural sectors. Regional growth, and changes in income and employment reacted directly to, and within the range and direction set by national economic activity. The simulations also lead to the conclusion that areal extent, infrastructure, and sector specific damages or impacts, as opposed to monetary losses, are the primary determinants of a disaster's effects upon employment, income, growth, and economic structure. ^

Surface mean flow and turbulence structure in tropical cyclone winds

Hurricanes are one of the deadliest and costliest natural hazards affecting the Gulf coast and Atlantic coast areas of the United States. An effective way to minimize hurricane damage is to strengthen structures and buildings. The investigation of surface level hurricane wind behavior and the resultant wind loads on structures is aimed at providing structural engineers with information on hurricane wind characteristics required for the design of safe structures. Information on mean wind profiles, gust factors, turbulence intensity, integral scale, and turbulence spectra and co-spectra is essential for developing realistic models of wind pressure and wind loads on structures. The research performed for this study was motivated by the fact that considerably fewer data and validated models are available for tropical than for extratropical storms. ^ Using the surface wind measurements collected by the Florida Coastal Monitoring Program (FCMP) during hurricane passages over coastal areas, this study presents comparisons of surface roughness length estimates obtained by using several estimation methods, and estimates of the mean wind and turbulence structure of hurricane winds over coastal areas under neutral stratification conditions. In addition, a program has been developed and tested to systematically analyze Wall of Wind (WoW) data, that will make it possible to perform analyses of baseline characteristics of flow obtained in the WoW. This program can be used in future research to compare WoW data with FCMP data, as gust and turbulence generator systems and other flow management devices will be used to create WoW flows that match as closely as possible real hurricane wind conditions. ^ Hurricanes are defined as tropical cyclones for which the maximum 1-minute sustained surface wind speeds exceed 74 mph. FCMP data include data for tropical cyclones with lower sustained speeds. However, for the winds analyzed in this study the speeds were sufficiently high to assure that neutral stratification prevailed. This assures that the characteristics of those winds are similar to those prevailing in hurricanes. For this reason in this study the terms tropical cyclones and hurricanes are used interchangeably. ^

Essays in environmental economic valuation and decision making in the presence of an environmental disaster

The first essay developed a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. I demonstrated by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrated that a simple extension of current DB-DC identifications derived explicitly from the Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provided caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirmed the simulation outcomes. The second essay applied a hedonic property value model to a unique water quality (WQ) dataset for a year-round, urban, and coastal housing market in South Florida, and found evidence that various WQ measures affect waterfront housing prices in this setting. However, the results indicated that this relationship is not consistent across any of the six particular WQ variables used, and is furthermore dependent upon the specific descriptive statistic employed to represent the WQ measure in the empirical analysis. These results continue to underscore the need to better understand both the WQ measure and its statistical form homebuyers use in making their purchase decision. The third essay addressed a limitation to existing hurricane evacuation modeling aspects by developing a dynamic model of hurricane evacuation behavior. A household's evacuation decision was framed as an optimal stopping problem where every potential evacuation time period prior to the actual hurricane landfall, the household's optimal choice is to either evacuate, or to wait one more time period for a revised hurricane forecast. A hypothetical two-period model of evacuation and a realistic multi-period model of evacuation that incorporates actual forecast and evacuation cost data for my designated Gulf of Mexico region were developed for the dynamic analysis. Results from the multi-period model were calibrated with existing evacuation timing data from a number of hurricanes. Given the calibrated dynamic framework, a number of policy questions that plausibly affect the timing of household evacuations were analyzed, and a deeper understanding of existing empirical outcomes in regard to the timing of the evacuation decision was achieved.

Carbon and nitrogen stable isotopic patterns in South Florida coastal ecosystems: Modern and paleoceanographic perspectives

Long term management plans for restoration of natural flow conditions through the Everglades increase the importance of understanding potential nutrient impacts of increased freshwater delivery on coastal biogeochemistry. The present study sought to increase understanding of the coastal marine system of South Florida under modern conditions and through the anthropogenic changes in the last century, on scales ranging from individual nutrient cycle processes to seasonal patterns in organic material (OM) under varying hydrodynamic regime, to century scale analysis of sedimentary records. In all applications, carbon and nitrogen stable isotopic compositions of OM were examined as natural recorders of change and nutrient cycling in the coastal system. ^ High spatial and temporal variability in stable isotopic compositions were observed on all time scales. During a transient phytoplankton bloom, δ 15N values suggested nitrogen fixation as a nutrient source supporting enhanced productivity. Seasonally, particulate organic material (POM) from ten sites along the Florida Reef Tract and in Florida Bay demonstrated variable fluctuations dependent on hydrodynamic setting. Three separate intra-annual patterns were observed, yet statistical differences were observed between groupings of Florida Bay and Atlantic Ocean sites. The POM δ 15N values ranged on a quarterly basis by 7‰, while δ 13C varied by 22‰. From a sediment history perspective, four cores collected from Florida Bay further demonstrated the spatial and temporal variability of the system in isotopic composition of bulk OM over time. Source inputs of OM varied with location, with terrestrial inputs dominating proximal to Everglades freshwater discharge, seagrasses dominating in open estuary cores, and a marine mixture of phytoplankton and seagrass in a core from the boundary zone between Florida Bay and the Gulf of Mexico. Significant shifts in OM geochemistry were observed coincident with anthropogenic events of the 20th century, including railroad and road construction in the Florida Keys and Everglades, and also the extensive drainage changes in Everglades hydrology. The sediment record also preserved evidence of the major hurricanes of the last century, with excursions in geochemical composition coincident with Category 4-5 storms. ^

Paleoenvironmental reconstruction of Florida Bay, South Florida, using benthic foraminifera

Efforts that are underway to rehabilitate the Florida Bay ecosystem to a more natural state are best guided by a comprehensive understanding of the natural versus human-induced variability that has existed within the ecosystem. Benthic foraminifera, which are well-known paleoenvironmental indicators, were identified in 203 sediment samples from six sediment cores taken from Florida Bay, and analyzed to understand the environmental variability through anthropogenically unaltered and altered periods. In this research, taxa serving as indicators of (1) seagrass abundance (which is correlated with water quality), (2) salinity, and (3) general habitat change, were studied in detail over the past 120 years, and more generally over the past ~4000 years. Historical seagrass abundance was reconstructed with the proportions of species that prefer living attached to seagrass blades over other substrates. Historical salinity trends were determined by analyzing brackish versus marine faunas, which were defined based on species’ salinity preferences. Statistical methods including cluster analysis, discriminant analysis, analysis of variance and Fisher’s α were used to analyze trends in the data. The changes in seagrass abundance and salinity over the last ~120 years are attributed to anthropogenic activities such as construction of the Flagler Railroad from the mainland to the Florida Keys, the Tamiami Trail that stretches from the east to west coast, and canals and levees in south Florida, as well as natural events such as droughts and increased rainfall from hurricanes. Longer term changes (over ~4000 years) in seagrass abundance and salinity are mostly related to sea level changes. Since seawater entered the Florida Bay area around ~4000 years ago, only one probable sea level drop occurring around ~3000 years was identified.

A Markov chain location-allocation meta-model for hurricane relief

An emergency is a deviation from a planned course of events that endangers people, properties, or the environment. It can be described as an unexpected event that causes economic damage, destruction, and human suffering. When a disaster happens, Emergency Managers are expected to have a response plan to most likely disaster scenarios. Unlike earthquakes and terrorist attacks, a hurricane response plan can be activated ahead of time, since a hurricane is predicted at least five days before it makes landfall. This research looked into the logistics aspects of the problem, in an attempt to develop a hurricane relief distribution network model. We addressed the problem of how to efficiently and effectively deliver basic relief goods to victims of a hurricane disaster. Specifically, where to preposition State Staging Areas (SSA), which Points of Distributions (PODs) to activate, and the allocation of commodities to each POD. Previous research has addressed several of these issues, but not with the incorporation of the random behavior of the hurricane's intensity and path. This research presents a stochastic meta-model that deals with the location of SSAs and the allocation of commodities. The novelty of the model is that it treats the strength and path of the hurricane as stochastic processes, and models them as Discrete Markov Chains. The demand is also treated as stochastic parameter because it depends on the stochastic behavior of the hurricane. However, for the meta-model, the demand is an input that is determined using Hazards United States (HAZUS), a software developed by the Federal Emergency Management Agency (FEMA) that estimates losses due to hurricanes and floods. A solution heuristic has been developed based on simulated annealing. Since the meta-model is a multi-objective problem, the heuristic is a multi-objective simulated annealing (MOSA), in which the initial solution and the cooling rate were determined via a Design of Experiments. The experiment showed that the initial temperature (T0) is irrelevant, but temperature reduction (δ) must be very gradual. Assessment of the meta-model indicates that the Markov Chains performed as well or better than forecasts made by the National Hurricane Center (NHC). Tests of the MOSA showed that it provides solutions in an efficient manner. Thus, an illustrative example shows that the meta-model is practical.

Predicting hurricane evacuation decisions: When, how many, and how far

Traffic from major hurricane evacuations is known to cause severe gridlocks on evacuation routes. Better prediction of the expected amount of evacuation traffic is needed to improve the decision-making process for the required evacuation routes and possible deployment of special traffic operations, such as contraflow. The objective of this dissertation is to develop prediction models to predict the number of daily trips and the evacuation distance during a hurricane evacuation. ^ Two data sets from the surveys of the evacuees from Hurricanes Katrina and Ivan were used in the models' development. The data sets included detailed information on the evacuees, including their evacuation days, evacuation distance, distance to the hurricane location, and their associated socioeconomic characteristics, including gender, age, race, household size, rental status, income, and education level. ^ Three prediction models were developed. The evacuation trip and rate models were developed using logistic regression. Together, they were used to predict the number of daily trips generated before hurricane landfall. These daily predictions allowed for more detailed planning over the traditional models, which predicted the total number of trips generated from an entire evacuation. A third model developed attempted to predict the evacuation distance using Geographically Weighted Regression (GWR), which was able to account for the spatial variations found among the different evacuation areas, in terms of impacts from the model predictors. All three models were developed using the survey data set from Hurricane Katrina and then evaluated using the survey data set from Hurricane Ivan. ^ All of the models developed provided logical results. The logistic models showed that larger households with people under age six were more likely to evacuate than smaller households. The GWR-based evacuation distance model showed that the household with children under age six, income, and proximity of household to hurricane path, all had an impact on the evacuation distances. While the models were found to provide logical results, it was recognized that they were calibrated and evaluated with relatively limited survey data. The models can be refined with additional data from future hurricane surveys, including additional variables, such as the time of day of the evacuation. ^

Development of methods for spatial modeling of sediments quality in Lake Okeechobee, Florida

The major objectives of this dissertation were to develop optimal spatial techniques to model the spatial-temporal changes of the lake sediments and their nutrients from 1988 to 2006, and evaluate the impacts of the hurricanes occurred during 1998–2006. Mud zone reduced about 10.5% from 1988 to 1998, and increased about 6.2% from 1998 to 2006. Mud areas, volumes and weight were calculated using validated Kriging models. From 1988 to 1998, mud thicknesses increased up to 26 cm in the central lake area. The mud area and volume decreased about 13.78% and 10.26%, respectively. From 1998 to 2006, mud depths declined by up to 41 cm in the central lake area, mud volume reduced about 27%. Mud weight increased up to 29.32% from 1988 to 1998, but reduced over 20% from 1998 to 2006. The reduction of mud sediments is likely due to re-suspension and redistribution by waves and currents produced by large storm events, particularly Hurricanes Frances and Jeanne in 2004 and Wilma in 2005. Regression, kriging, geographically weighted regression (GWR) and regression-kriging models have been calibrated and validated for the spatial analysis of the sediments TP and TN of the lake. GWR models provide the most accurate predictions for TP and TN based on model performance and error analysis. TP values declined from an average of 651 to 593 mg/kg from 1998 to 2006, especially in the lake’s western and southern regions. From 1988 to 1998, TP declined in the northern and southern areas, and increased in the central-western part of the lake. The TP weights increased about 37.99%–43.68% from 1988 to 1998 and decreased about 29.72%–34.42% from 1998 to 2006. From 1988 to 1998, TN decreased in most areas, especially in the northern and southern lake regions; western littoral zone had the biggest increase, up to 40,000 mg/kg. From 1998 to 2006, TN declined from an average of 9,363 to 8,926 mg/kg, especially in the central and southern regions. The biggest increases occurred in the northern lake and southern edge areas. TN weights increased about 15%–16.2% from 1988 to 1998, and decreased about 7%–11% from 1998 to 2006.

An assessment of natural and human disturbance effects on Mexican ecosystems: current trends and research gaps

Mexico harbors more than 10% of the planet’s endemic species. However, the integrity and biodiversity of many ecosystems is experiencing rapid transformation under the influence of a wide array of human and natural disturbances. In order to disentangle the effects of human and natural disturbance regimes at different spatial and temporal scales, we selected six terrestrial (temperate montane forests, montane cloud forests, tropical rain forests, tropical semi-deciduous forests, tropical dry forests, and deserts) and four aquatic (coral reefs, mangrove forests, kelp forests and saline lakes) ecosystems. We used semiquantitative statistical methods to assess (1) the most important agents of disturbance affecting the ecosystems, (2) the vulnerability of each ecosystem to anthropogenic and natural disturbance, and (3) the differences in ecosystem disturbance regimes and their resilience. Our analysis indicates a significant variation in ecological responses, recovery capacity, and resilience among ecosystems. The constant and widespread presence of human impacts on both terrestrial and aquatic ecosystems is reflected either in reduced area coverage for most systems, or reduced productivity and biodiversity, particularly in the case of fragile ecosystems (e.g., rain forests, coral reefs). In all cases, the interaction between historical human impacts and episodic high intensity natural disturbance (e.g., hurricanes, fires) has triggered a reduction in species diversity and induced significant changes in habitat distribution or species dominance. The lack of monitoring programs assessing before/after effects of major disturbances in Mexico is one of the major limitations to quantifying the commonalities and differences of disturbance effects on ecosystem properties.

Disaster Risk Management Disparity in the Caribbean: Evidence from Barbados, Dominican Republic, Jamaica and Trinidad and Tobago

This study on risk and disaster management capacities of four Caribbean countries: Barbados, the Dominican Republic, Jamaica, and Trinidad and Tobago, examines three main dimensions: 1) the impact of natural disasters from 1900 to 2010 (number of events, number of people killed, total number affected, and damage in US$); 2) institutional assessments of disaster risk management disparity; and 3) the 2010 Inter-American Bank for Development (IADB) Disaster Risk and Risk Management indicators for the countries under study. The results show high consistency among the different sources examined, pointing out the need to extend the IADB measurements to the rest of the Caribbean countries. Indexes and indicators constitute a comparison measure vis-à-vis existing benchmarks in order to anticipate a capacity to deal with adverse events and their consequences; however, the indexes and indicators could only be tested against the occurrence of a real event. Therefore, the need exists to establish a sustainable and comprehensive evaluation system after important disasters to assess a country‘s performance, verify the indicators, and gain feedback on measurement systems and methodologies. There is diversity in emergency and preparedness for disasters in the four countries under study. The nature of the event (hurricanes, earthquakes, floods, and seismic activity), especially its frequency and the intensity of the damage experienced, is related to how each has designed its risk and disaster management policies and programs to face natural disasters. Vulnerabilities to disaster risks have been increasing, among other factors, because of uncontrolled urbanization, demographic density and poverty increase, social and economic marginalization, and lack of building code enforcement. The four countries under study have shown improvements in risk management capabilities, yet they are far from being completed prepared. Barbados‘ risk management performance is superior, in comparison, to the majority of the countries of the region. However, is still far in achieving high performance levels and sustainability in risk management, primarily when it has the highest gap between potential macroeconomic and financial losses and the ability to face them. The Dominican Republic has shown steady risk performance up to 2008, but two remaining areas for improvement are hazard monitoring and early warning systems. Jamaica has made uneven advances between 1990 and 2008, requiring significant improvements to achieve high performance levels and sustainability in risk management, as well as macroeconomic mitigation infrastructure. Trinidad and Tobago has the lowest risk management score of the 15 countries in the Latin American and Caribbean region as assessed by the IADB study in 2010, yet it has experienced an important vulnerability reduction. In sum, the results confirmed the high disaster risk management disparity in the Caribbean region.