Understanding The Decision-Making Process of Local Level Emergency Managers and Future Impacts of Social Data

During the course of a natural disaster, affected populations turn to different avenues to attempt to communicate their needs and locations while emergency managers are faced with the task of making quick decisions to aid in the response effort. The decisions that emergency managers face are affected by factors such as available resources, responder safety, and source of information. In this research, we interview emergency managers about the 2009 North American Ice Storm and a flooding event in late April of 2017 to understand the decisions made and the factors that affected these decisions. Using these interviews, a list of interview questions using the Critical Decision Method were created that could be used to more deeply understand the decisions and decision-making process of a local-level emergency manager during a disaster response event. Additionally, animations were created to illustrate the comparative effectiveness of disaster response routing plans developed with and without the consideration of social data based on data inspired by a real event

Circulation

Circulation is important to distributions of salt, of deep-ocean heat and hence regional climate, of pollutants and of many species carried by the flow during their lifecycle. Currents affect offshore operations and habitats. Five sections from 1957 to 2004 suggest decline of the Atlantic Meridional Overturning Circulatin (AMOC) but this is within the range of large variability on time-scales of weeks to months. An overall trend has not been determined from the continuous measurements begun in 2004. Deep outflows of cold water from the Nordic seas are likewise too variable to infer any overall trend. Strong North Atlantic flow eastwards towards the UK may correlate with positive North Atlantic Oscillation (NAO) Index (i.e. prevailing westerly winds). Enhanced along-slope current around the UK may correlate with a negative NAO Index. Climate models’ consensus makes it very likely that AMOC will decrease over the next century, but not ‘shut down’ completely. Similar spatial and temporal variability (arising from complex topography and variable forcing) is likely in future

Development of a time-dependent, audio-visual, stated choice method of data collection for hurricane evacuation behavior

Revealed preference is the traditional method to collect hurricane evacuation behavior data. However, revealed preference surveys, as they are currently administered, have the disadvantage that they are unable to collect time-sensitive and policy-sensitive data needed to test evacuation policies. In contrast, data collected from a time-dependent, stated-choice survey will allow researchers to collect not only time-sensitive and policy-sensitive data but also information that will allow testing potential new evacuation policies. However, no research has been conducted to establish the methodology of such a survey. To fill the gap, this study was conducted to develop a new time-dependent, audio-visual, stated-choice method to collect evacuation behavior data. To achieve the objective, nine animations of hypothetical storms were developed based on recent hurricane history. To test the new methodology and its effectiveness, data was collected using both new and traditional methods and their cost and ability to produce good evacuation models were compared. In the new method survey respondents had to watch animations of storm scenarios and answer questions related to their intended behavior while in the traditional method they reported on their behavior in hurricane Gustav that made landfall near New Orleans in 2008. Results indicate that the new stated-choice method is easy to use and effective in collecting time-dependent and policy-sensitive data but costs 25 percent more than the traditional method. The new method appears to have the potential of evolving into a survey instrument that can be used by researchers and practitioners working in hurricane evacuation modeling

EVALUATION OF DIFFERENT CONTRA-FLOW STRATEGIES FOR HURRICANE EVACUATION IN CHARLESTON, SOUTH CAROLINA

The number of category four and five hurricanes has nearly doubled over the past decade. Charleston, the second most populous city in South Carolina, is located on a very low peninsula, making it susceptible to floods during hurricanes and storm surges. In the event of a hurricane, the population at-risk must be evacuated to safety as quickly as possible. The Interstate system is the primary mode to evacuate at-risk population out of Charleston. Effective traffic management strategies are needed to manage the significant increase in demand on highways during the evacuation and contra-flowing traffic has been applied as a strategy to meet this need. This study evaluated the reduction in delay by proposing a new ramp and implementing different contra-flow strategies, such as contra-flowing one-lane, two-lanes and all lanes for traffic demand management during evacuation along the I-26 corridor out of Charleston using a microscopic simulation tool called PARAMICS

Port Infrastructure Resilience through Combined Wind-Surge Demand Characterization

The United States economy is reliant on maritime transportation for 70% of imports and exports. Structures that are integral to the operation of ports, such as cranes, are jeopardized when tropical storms approach land. While wind is the only environmental load used to design dockside container cranes, storm surge often accompanies severe wind events and can create large structural loads. This study focuses on determining coupled storm-surge demands and the effect of waves on dockside container cranes. A damage index prediction tool that considers both maximum wind speed and storm surge height is developed and applied to historical hurricane data for effectiveness. Comparisons of the new damage index with traditional damage indices based solely on wind-speed indicate that the coupled wind-surge model more accurately represented the damage of the selected hurricanes. Analytical models in a parametric study investigate the influence of combined wind and water forces on port-type structures and an experimental model is created to validate the analytical results. Results from the parametric investigations indicate that when surge conditions are considered, wave height and wave type have more impact on the structural demands than wind speed. For loading scenarios impacted by surge, there was no identifiable increase in stress on the structure when wind speed increased. The developed wind-surge damage index and analytical model findings suggest that both storm surge and wave loading should be considered in port infrastructure design to reduce damage costs and improve resiliency

Ethical Issues in Engineering Models: Personal Reflections

I start this contribution with an overview of my personal involvement—as an Operations Research consultant—in several engineering case-studies that may raise ethical questions; these case studies employ simulation models. Next, I present an overview of the recent literature on ethical issues in modeling, focusing on the validation of the model’s assumptions; the decisive role of these assumptions leads to the quest for robust models. Actually, models are meant to solve practical problems; these problems may have ethical implications for the various stakeholders; namely, modelers, clients, and the public at large. Finally, I briefly discuss whistle blowing.ethics;code of conduct;stakeholders;validity;risk analysis;simulation;operations research

Modeling Decision Making Related to Incident Delays During Hurricane Evacuations

Successful evacuations from metropolitan areas require optimizing the transportation network, monitoring conditions, and adapting to changes. Evacuation plans seek to maximize the city\u27s ability to evacuate traffic to flee the endangered region, but once an evacuation begins, real time events degrade even the best plans. To better understand behavioral responses made during a hurricane evacuation, a survey of potential evacuees obtained data on demographics, driving characteristics, and the traffic information considered prior to and during an evacuation. Analysis showed significant levels of correlation between demographic factors (e.g., gender, age, social class, etc.) and self-assessed driver characteristics, but limited correlation with the decision to take an alternate route. Survey results suggest evacuees\u27 decisions to divert are functions of the length of time a driver has been in congestion, the amount of travel information provided, and its method of delivery. This association differs significantly from those identified by other studies that focused on routine, non-evacuation, conditions. A decision-making model that forecasts decision tendencies using these factors was created. The model was integrated in and tested using a dynamic evacuation simulation. The combined model and simulation allow assessment of the impacts traveler information content, timing, and method of delivery have on traffic flow and evacuation times, imitating the impact of traffic information systems. The effectiveness of alternate route use was assessed by measurements of total vehicle volumes processed and queue persistence. Effectiveness was highly dependent on the road network in the immediate vicinity, especially the number of accesses to the alternate route and vehicle capacity on the alternate route and accesses. Integration of the decision-making model in a dynamic hurricane evacuation simulation is unique to this study. This study yields a greater understanding of evacuee decisions and factors associated with related travel decisions. It provides the novel integration of a behavioral model and a dynamic evacuation simulation, increasing the realism of evacuation planning and providing a valuable tool supporting the decision process. Understanding gained may contribute to reduced evacuation times and enhanced public safety

Spartan Daily, September 22, 2005

Volume 125, Issue 16https://scholarworks.sjsu.edu/spartandaily/10159/thumbnail.jp

Exploratory Assessment of Roadway Infrastructure Adaptation to the Impacts of Sea-level Rise

Transportation agencies in coastal urban areas face a significant challenge to enhance the long-term resilience of their networks to flooding and storm surge events exacerbated by sea level rise. The problem of sea-level rise adaptation is characterized by deep uncertainty that makes it complex to assess the value of adaptation investments. To enable informed adaptation decisions, the present study created a dynamic stochastic modeling framework based on the theoretical underpinnings of complex adaptive systems that integrates: (i) stochastic simulation of sea-level rise stressors based on the data obtained from downscaled climate studies pertaining to future projections of sea-level and precipitation; (ii) dynamic modeling of roadway conditions by considering regular decay of roadways, as well as structural damages caused by storm surge events; and (iii) a decision-theoretic modeling of agency infrastructure management and adaptation processes based on cognitive psychology, bounded rationality, and regret theories. In this framework, resilience is examined based on trend changes in the network performance measures (e.g., life cycle costs and performance). The created framework and model were tested in a case study related to the road network of the city of Miami-Beach, which global assessments rank first iv among the world\u27s urban areas most exposed to sea-level rise risks. The results indicated that: (i) SLR Adaptation investment and life cycle costs of roadway infrastructure are negatively correlated. In addition, it was shown that the sensitivity of network’s life cycle cost to actual sea-level rise scenario decreases when adaptation investment increases. These finding emphasize the importance of proactive improvement of the network resilience to alleviate the long-term costs of sea-level rise. (ii) When funding is sufficient for all required adaptation actions, mid-term adaptation planning yields lower life cycle cost. When funding is insufficient, aggregated investment in long-term adaptation planning intervals yields lower network LCC. These findings imply that different adaptation planning approaches should be taken for different levels of adaptation investment. (iii) The agency’s perception of SLR and risk attitude do not have significant effect on life cycle cost of roadway networks. Hence, implementation of adaptation action based on any perception of sea-level rise and risk attitude can significantly reduce the life cycle costs of roadway networks under the impacts of SLR. (iv) The devised performance target has negative correlation with life cycle cost of a roadway network affected by SLR impacts. Therefore, compromising the network performance condition will never result in lower life cycle costs