14-07 Development of Decision Support Tools to Assess Pedestrian and Bicycle Safety: Focus on Population, Demographic and Socioeconomic Spectra

Despite the increase of these non-motorized trips, bicyclists and pedestrians remain vulnerable road users that are often over represented in traffic crashes. While the currently used methods that identify hazardous locations serve their purpose well, majority represent a reactive approach that seeks improvement after crashes happen. This research addressed these issues and proposed decision support tools to aid the implementation of bicycle and pedestrian safety strategies. This work developed an access based tool to predict the expected number of crashes at different neighborhood levels. This tool combines the traditional methods such as those provided in the Highway Safety manual to predict the expected number of bicycle and pedestrian crashes. First, a cluster analysis technique is proposed and developed a Geographic Information Systems (GIS) technique to facilitate the identification of high crash locations. Safety Performance Functions (SPFs) are developed in form of mathematical equations to relate the number of crashes to area socioeconomic and demographic characteristics. An integrated system consisting of access database and safety performance functions, and whose interface is designed to automatically compute the number of crashes given the input values is developed. Basing on crash value, the tool can be adopted as a framework to guide the appropriate allocation of safety improvement resources

Effect of Varying Wind Intensity, Forward Speed, and Surface Pressure on Storm Surges of Hurricane RitaEffect of Varying Wind Intensity, Forward Speed, and Surface Pressure on Storm Surges of Hurricane Rita

Hurricane storm surges are influenced by several factors, including wind intensity, surface pressure, forward speed, size, angle of approach, ocean bottom depth and slope, shape and geographical features of the coastline. The relative influence of each factor may be amplified or abated by other factors that are acting at the time of the hurricane’s approach to the land. To understand the individual and combined influence of wind intensity, surface pressure and forward speed, a numerical experiment is conducted using Advanced CIRCulation + Simulating Waves Nearshore (ADCIRC + SWAN) by performing hindcasts of Hurricane Rita storm surges. The wind field generated by Ocean Weather Inc. (OWI) is used as the base meteorological forcing in ADCIRC + SWAN. All parameters are varied by certain percentages from those in the OWI wind field. Simulation results are analyzed for maximum wind intensity, wind vector pattern, minimum surface pressure, forward speed, maximum water elevation, station water elevation time series, and high water marks. The results for different cases are compared against each other, as well as with observed data. Changes in the wind intensity have the greatest impact, followed by the forward speed and surface pressure. The combined effects of the wind intensity and forward speed are noticeably different than their individual effects

Understanding the Effects of Wind Intensity, Forward Speed, Pressure and Track on Generation and Propagation of Hurricane Irma Surges around Florida

In this study, it is demonstrated that hurricane wind intensity, forward speed, pressure, and track play an important role on the generation and propagation of coastal storm surges. Hurricane Irma, which heavily impacted the entire Florida peninsula in 2017, is used to study the storm surge sensitivity to varying storm characteristics. Results show that the west coast experiences a negative surge due to offshore wind of the approaching storm, but the positive surge returns after the hurricane eye passes over a location and wind became onshore. In the west coast peak, surges are intensified by an increase in onshore wind intensity and forward speed. In the Florida Keys, peak surges are intensified by an increase in wind intensity, a decrease in forward speed and a decrease in pressure. In southeast and east Florida, peak surges are intensified by decrease in pressure, although overall surges are less significant as the water can slide along the coastline. In the recessed coastline of Georgia-Carolinas, maximum surge is elevated by an increase in onshore wind intensity. Shifting the track westward increases peak surges on the west coast, while shifting the track eastward increases peak surge on the east coast. The results demonstrate a new understanding about the sensitivity of surge to varying parametric conditions and the importance of considering changes in the coastline orientation in storm surge predictions

Understanding Hurricane Storm Surge Generation and Propagation: The Case of Hurricane Rita

Damage due to hurricane storm surges remains a serious concern for coastal zones. As the world’s coastal communities continue to experience the highest population growth with rapid urbanization, economic activities and tourism, storm surge and overland flooding will invariably continue to pose high coastal risk for human life and property damage. To minimize future risk for damage, it is imperative that accurate storm surge models be developed to reliably forecast actual events. One important aspect of improving the accuracy of storm surge modelling is understanding the effect of bottom friction, wind drag and meteorological forcing on storm surge generation and propagation. Moreover, hurricane storm surges are influenced by several factors, including wind intensity, central pressure and forward speed, size, angle of approach, shape of coastline, ocean bottom depth and slope, geographical features, etc. The relative influence of each factor may be amplified or abated by other factors acting at the time of the hurricane’s approach to the land. The goal of this study is to examine the impacts of Hurricane Rita in 2005 on the Unites States coast on the Gulf of Mexico, by conducting numerical experiments to evaluate the effect of bottom friction, wind drag and meteorological forcing using ADCIRC+SWAN and parameterizing meteorological inputs namely, intensity, pressure and forward speed in Oceanweather Inc, a parametric wind model. The United States Geological Survey (USGS) and National Oceanic and Atmospheric Administration (NOAA) observation data along the Gulf coast are used for model validation. Results of this study can be useful in understanding the importance of bottom friction, wind drag and meteorological forcing. In addition, this dissertation labor to evaluate the effect of varying wind intensity, forward speed, and pressure for Hurricane Rita. The new parameterizations for bottom friction, wind drag, wind intensity, forward speed, and pressure developed by this dissertation can serve as a foundation for improving the accuracy of storm surge prediction

Effect of Varying Wind Intensity, Forward Speed, and Surface Pressure on Storm Surges of Hurricane Rita

Hurricane storm surges are influenced by several factors, including wind intensity, surface pressure, forward speed, size, angle of approach, ocean bottom depth and slope, shape and geographical features of the coastline. The relative influence of each factor may be amplified or abated by other factors that are acting at the time of the hurricane’s approach to the land. To understand the individual and combined influence of wind intensity, surface pressure and forward speed, a numerical experiment is conducted using Advanced CIRCulation + Simulating Waves Nearshore (ADCIRC + SWAN) by performing hindcasts of Hurricane Rita storm surges. The wind field generated by Ocean Weather Inc. (OWI) is used as the base meteorological forcing in ADCIRC + SWAN. All parameters are varied by certain percentages from those in the OWI wind field. Simulation results are analyzed for maximum wind intensity, wind vector pattern, minimum surface pressure, forward speed, maximum water elevation, station water elevation time series, and high water marks. The results for different cases are compared against each other, as well as with observed data. Changes in the wind intensity have the greatest impact, followed by the forward speed and surface pressure. The combined effects of the wind intensity and forward speed are noticeably different than their individual effects

Associating Pedestrian Crashes with Demographic and Socioeconomic Factors

© 2018 World Conference on Transport Research Society In the last decade, the concept of walkable neighborhoods has emerged as a topic of great interest. However, it is still unclear about the influence of socioeconomic and demographic factors on pedestrian crashes. This study proposed a methodology for pedestrian crash analysis that combines Geographic Information System (GIS) methods and statistical analysis to study the influence of socioeconomic and demographic factors on the occurrence of pedestrian crashes. The analysis was based on statewide crash data collected in Tennessee from 2008 to 2012. First, GIS kernel density technique was proposed to identify high concentration of pedestrian crash clusters and results were presented using cases studies of Davidson and Hamilton counties. GIS analysis identified pedestrian crash clusters among block groups with a high population who walk to work and block groups with a high number of housing units with no vehicles. A negative binomial model was applied using a statewide data to test the statistical significance of explanatory variables. As expected, model results indicated that population density, population from 15 to 64 years of age, high population of neighborhoods commuting to work by walking (without adequate facilities supporting pedestrians such as sidewalks and crosswalks) and high population of neighborhoods of housing units with no vehicles significantly increase the number of pedestrian crashes. However, blocks whose streets have adequate presence of median, shoulders, and sidewalks had negative coefficients hence their presence tends to decrease pedestrian crashes. Furthermore population commuting to work by private cars and high median household income significantly reduces pedestrian crash frequency. The findings from Kernel density and statistical modeling are relatively identical in the sense that all found household vehicle availability to be a factor in influencing frequency of pedestrian crashes. The findings of this study can assist in implementation of proactive pedestrian safety strategies

Effect of Bottom Friction, Wind Drag Coefficient, and Meteorological Forcing in Hindcast of Hurricane Rita Storm Surge Using SWAN + ADCIRC Model

An evaluation of the effect of bottom friction, wind drag coefficient, and meteorological forcing is conducted using a tightly coupled wave and circulation model, SWAN + ADCIRC (i.e., Simulating WAves Nearshore + ADvanced CIRCulation), to hindcast the storm surge of Hurricane Rita (2005). Wind drag coefficient formulations of Powell, Zijlema, and Peng & Li are used to calculate wind stresses. Bottom friction and wind drag coefficients are systematically increased and decreased to quantify their impacts on the hindcast. Different meteorological forcing options are applied to study the effect of wind fields on storm surge development and propagation. Simulated water levels are compared with observed data collected from about 150 locations. It is evident that a lower bottom friction causes higher and faster surge propagation, and earlier arrival of inundation peak at locations far from the land fall. Drag coefficients of Powell, with or without a cap of 0.002, and Zijlema produce similar results, while that of Peng & Li slightly overpredicted the surge. Wind fields may cause overprediction or underprediction of the surge, depending on the choice of the wind model. A good agreement is found between Zijlema’s findings and this study; that simultaneously decreasing or increasing both bottom friction and wind drag essentially provides the same hindcast results

Evaluation of Wave Contributions in Hurricane Irma Storm Surge Hindcast

This paper evaluates the contribution of waves to the total predicted storm surges in a Hurricane Irma hindcast, using ADCIRC+SWAN and ADCIRC models. The contribution of waves is quantified by subtracting the water levels hindcasted by ADCIRC from those hindcasted by ADCIRC+SWAN, using OWI meteorological forcing in both models. Databases of water level time series, wave characteristic time series, and high-water marks are used to validate the model performance. Based on the application of our methodology to the coastline around Florida, a peninsula with unique geomorphic characteristics, we find that wave runup has the largest contribution to the total water levels on the south and northeast coasts. Waves increase the surge on the south and northeast coasts, due to large fetch and wave runups. On the west coast, the wave effect is not significant, due to limited fetch. However, significant wave heights become greater as the waves propagate into the deep inner gulf. The continental shelf on Florida’s west coast plays a critical role in decreasing the significant wave height and sheltering the coastal areas from large wave effects. Both models underpredict the high-water marks, but ADCIRC+SWAN reduces the underprediction and improves the parity with the observed data, although the scatter is slightly higher than that of ADCIRC

Evaluation of Wave Contributions in Hurricane Irma Storm Surge Hindcast

This paper evaluates the contribution of waves to the total predicted storm surges in a Hurricane Irma hindcast, using ADCIRC+SWAN and ADCIRC models. The contribution of waves is quantified by subtracting the water levels hindcasted by ADCIRC from those hindcasted by ADCIRC+SWAN, using OWI meteorological forcing in both models. Databases of water level time series, wave characteristic time series, and high-water marks are used to validate the model performance. Based on the application of our methodology to the coastline around Florida, a peninsula with unique geomorphic characteristics, we find that wave runup has the largest contribution to the total water levels on the south and northeast coasts. Waves increase the surge on the south and northeast coasts, due to large fetch and wave runups. On the west coast, the wave effect is not significant, due to limited fetch. However, significant wave heights become greater as the waves propagate into the deep inner gulf. The continental shelf on Florida’s west coast plays a critical role in decreasing the significant wave height and sheltering the coastal areas from large wave effects. Both models underpredict the high-water marks, but ADCIRC+SWAN reduces the underprediction and improves the parity with the observed data, although the scatter is slightly higher than that of ADCIRC

Understanding Hurricane Storm Surge Generation and Propagation Using a Forecasting Model, Forecast Advisories and Best Track in a Wind Model, and Observed Data—Case Study Hurricane Rita

Meteorological forcing is the primary driving force and primary source of errors for storm surge forecasting. The objective of this study was to learn how forecasted meteorological forcing influences storm surge generation and propagation during a hurricane so that storm surge models can be reliably used to forecast actual events. Hindcasts and forecasts of Hurricane Rita (2005) storm surge was used as a case study. Meteorological forcing or surface wind/pressure fields for Hurricane Rita were generated using both the Weather Research and Forecasting (WRF) full-scale forecasting model along with archived hurricane advisories ingested into a sophisticated parametric wind model, namely Generalized Asymmetric Holland Model (GAHM). These wind fields were used to forecast Rita storm surges. Observation based wind fields from the OceanWeather Inc. (OWI) Interactive Objective Kinematic Analysis (IOKA) model, and Best track wind data ingested into the GAHM model were used to generate wind fields for comparison purposes. These wind fields were all used to hindcast Rita storm surges with the ADvanced CIRCulation (ADCIRC) model coupled with the Simulating Waves Nearshore (SWAN) model in a tightly coupled storm surge-wave model referred to as ADCIRC+SWAN. The surge results were compared against a quality-controlled database of observed data to assess the performance of these wind fields on storm surge generation and propagation. The surge hindcast produced by the OWI wind field performed the best, although some high water mark (HWM) locations were overpredicted. Although somewhat underpredicted, the WRF wind fields forecasted wider surge extent and wetted most HWM locations. The hindcast using the Best track parameters in the GAHM and the forecast using forecast/advisories from the National Hurricane Center (NHC) in the GAHM produced strong and narrow wind fields causing localized high surges, which resulted in overprediction near landfall while many HWM locations away from wind bands remained dry