Development of test-based wind-driven rain intrusion model for hurricane-induced building interior and contents damage

Major portion of hurricane-induced economic loss originates from damages to building structures. The damages on building structures are typically grouped into three main categories: exterior, interior, and contents damage. Although the latter two types of damages, in most cases, cause more than 50% of the total loss, little has been done to investigate the physical damage process and unveil the interdependence of interior damage parameters. Building interior and contents damages are mainly due to wind-driven rain (WDR) intrusion through building envelope defects, breaches, and other functional openings. The limitation of research works and subsequent knowledge gaps, are in most part due to the complexity of damage phenomena during hurricanes and lack of established measurement methodologies to quantify rainwater intrusion. This dissertation focuses on devising methodologies for large-scale experimental simulation of tropical cyclone WDR and measurements of rainwater intrusion to acquire benchmark test-based data for the development of hurricane-induced building interior and contents damage model. Target WDR parameters derived from tropical cyclone rainfall data were used to simulate the WDR characteristics at the Wall of Wind (WOW) facility. The proposed WDR simulation methodology presents detailed procedures for selection of type and number of nozzles formulated based on tropical cyclone WDR study. The simulated WDR was later used to experimentally investigate the mechanisms of rainwater deposition/intrusion in buildings. Test-based dataset of two rainwater intrusion parameters that quantify the distribution of direct impinging raindrops and surface runoff rainwater over building surface — rain admittance factor (RAF) and surface runoff coefficient (SRC), respectively —were developed using common shapes of low-rise buildings. The dataset was applied to a newly formulated WDR estimation model to predict the volume of rainwater ingress through envelope openings such as wall and roof deck breaches and window sill cracks. The validation of the new model using experimental data indicated reasonable estimation of rainwater ingress through envelope defects and breaches during tropical cyclones. The WDR estimation model and experimental dataset of WDR parameters developed in this dissertation work can be used to enhance the prediction capabilities of existing interior damage models such as the Florida Public Hurricane Loss Model (FPHLM).^

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.

Chilling damage in a changing climate in coastal landscapes of the subtropical zone: a case study from south Florida

Extensive portions of the southern Everglades are characterized by series of elongated, raised peat ridges and tree islands oriented parallel to the predominant flow direction, separated by intervening sloughs. Tall herbs or woody species are associated with higher elevations and shorter emergent or floating species are associated with lower elevations. The organic soils in this “Ridge-and-Slough” landscape have been stable over millennia in many locations, but degrade over decades under altered hydrologic conditions. We examined soil, pore water, and leaf phosphorus (P) and nitrogen (N) distributions in six Ridge and Slough communities in Shark Slough, Everglades National Park. We found P enrichment to increase and N to decrease monotonically along a gradient from the most persistently flooded sloughs to rarely flooded ridge environments, with the most dramatic change associated with the transition from marsh to forest. Leaf N:P ratios indicated that the marsh communities were strongly P-limited, while data from several forest types suggested either N-limitation or co-limitation by N and P. Ground water stage in forests exhibited a daytime decrease and partial nighttime recovery during periods of surface exposure. The recovery phase suggested re-supply from adjacent flooded marshes or the underlying aquifer, and a strong hydrologic connection between ridge and slough. We therefore developed a simple steady-state model to explore a mechanism by which a phosphorus conveyor belt driven by both evapotranspiration and the regional flow gradient can contribute to the characteristic Ridge and Slough pattern. The model demonstrated that evapotranspiration sinks at higher elevations can draw in low concentration marsh waters, raising local soil and water P concentrations. Focusing of flow and nutrients at the evapotranspiration zone is not strong enough to overcome the regional gradient entirely, allowing the nutrient to spread downstream and creating an elongated concentration plume in the direction of flow. Our analyses suggest that autogenic processes involving the effects of initially small differences in topography, via their interactions with hydrology and nutrient availability, can produce persistent physiographic patterns in the organic sediments of the Everglades.

Chilling damage in a changing climate in coastal landscapes of the subtropical zone: a case study from south Florida

Freeze events significantly influence landscape structure and community composition along subtropical coastlines. This is particularly true in south Florida, where such disturbances have historically contributed to patch diversity within the mangrove forest, and have played a part in limiting its inland transgression. With projected increases in mean global temperatures, such instances are likely to become much less frequent in the region, contributing to a reduction in heterogeneity within the mangrove forest itself. To understand the process more clearly, we explored the dynamics of a Dwarf mangrove forest following two chilling events that produced freeze-like symptoms, i.e., leaf browning, desiccation, and mortality, and interpreted the resulting changes within the context of current winter temperatures and projected future scenarios. Structural effects from a 1996 chilling event were dramatic, with mortality and tissue damage concentrated among individuals comprising the Dwarf forest's low canopy. This disturbance promoted understory plant development and provided an opportunity for Laguncularia racemosa to share dominance with Rhizophora mangle. Mortality due to the less severe 2001 event was greatest in the understory, probably because recovery of the protective canopy following the earlier freeze was still incomplete. Stand dynamics were static over the same period in nearby unimpacted sites. The probability of reaching temperatures as low as those recorded at a nearby meteorological station (≤3 °C) under several warming scenarios was simulated by applying 1° incremental temperature increases to a model developed from a 42-year temperature record. According to the model, the frequency of similar chilling events decreased from once every 1.9 years at present to once every 3.4 and 32.5 years with 1 and 4 °C warming, respectively. The large decrease in the frequency of these events would eliminate an important mechanism that maintains Dwarf forest structure, and promotes compositional diversity.

Contribution of lipophilic secondary metabolites to the toxicity of strains of freshwater cyanobacterial harmful algal blooms, identified using the zebrafish (Danio rerio) embryo as a model for vertebrate development

Cyanobacteria ("blue-green algae") are known to produce a diverse repertoire of biologically active secondary metabolites. When associated with so-called "harmful algal blooms", particularly in freshwater systems, a number of these metabolites have been associated—as "toxins", or commonly "cyanotoxins"—with human and animal health concerns. In addition to the known water-soluble toxins from these genera (i.e. microcystins, cylindrospermopsin, and saxitoxins), our studies have shown that there are metabolites within the lipophilic extracts of these strains that inhibit vertebrate development in zebrafish embryos. Following these studies, the zebrafish embryo model was implemented in the bioassay-guided purification of four isolates of cyanobacterial harmful algal blooms, namely Aphanizomenon, two isolates of Cylindrospermopsis, and Microcystis, in order to identify and chemically characterize the bioactive lipophilic metabolites in these isolates. ^ We have recently isolated a group of polymethoxy-1-alkenes (PMAs), as potential toxins, based on the bioactivity observed in the zebrafish embryos. Although PMAs have been previously isolated from diverse cyanobacteria, they have not previously been associated with relevant toxicity. These compounds seem to be widespread across the different genera of cyanobacteria, and, according to our studies, suggested to be derived from the polyketide biosynthetic pathway which is a common synthetic route for cyanobacterial and other algal toxins. Thus, it can be argued that these metabolites are perhaps important contributors to the toxicity of cyanobacterial blooms. In addition to the PMAs, a set of bioactive glycosidic carotenoids were also isolated because of their inhibition of zebrafish embryonic development. These pigmented organic molecules are found in many photosynthetic organisms, including cyanobacteria, and they have been largely associated with the prevention of photooxidative damage. This is the first indication of these compounds as toxic metabolites and the hypothesized mode of action is via their biotransformation to retinoids, some of which are known to be teratogenic. Additional fractions within all four isolates have been shown to contain other uncharacterized lipophilic toxic metabolites. This apparent repertoire of lipophilic compounds may contribute to the toxicity of these cyanobacterial harmful algal blooms, which were previously attributed primarily to the presence of the known water-soluble toxins.^

Does the Pareto Distribution of Hurricane Damage Inherit its Fat Tail from a Zipf Distribution of Assets at Hazard?

Tropical Cyclones are a continuing threat to life and property. Willoughby (2012) found that a Pareto (power-law) cumulative distribution fitted to the most damaging 10% of US hurricane seasons fit their impacts well. Here, we find that damage follows a Pareto distribution because the assets at hazard follow a Zipf distribution, which can be thought of as a Pareto distribution with exponent 1. The Z-CAT model is an idealized hurricane catastrophe model that represents a coastline where populated places with Zipf- distributed assets are randomly scattered and damaged by virtual hurricanes with sizes and intensities generated through a Monte-Carlo process. Results produce realistic Pareto exponents. The ability of the Z-CAT model to simulate different climate scenarios allowed testing of sensitivities to Maximum Potential Intensity, landfall rates and building structure vulnerability. The Z-CAT model results demonstrate that a statistical significant difference in damage is found when only changes in the parameters create a doubling of damage.