The Flood Mitigation Problem in a Road Network

Natural disasters are highly complex and unpredictable. However, long-term planning and preparedness activities can help to mitigate the consequences and reduce the damage. For example, in cities with a high risk of flooding, appropriate roadway mitigation can help reduce the impact of floods or high waters on transportation systems. Such communities could benefit from a comprehensive assessment of mitigation on road networks and identification of the best subset of roads to mitigate. In this study, we address a pre-disaster planning problem that seeks to strengthen a road network against flooding. We develop a network design problem that maximizes the improvement in accessibility and travel times between population centers and healthcare facilities subject to a given budget. We provide techniques for reducing the problem size to help make the problem tractable. We use cities in the state of Iowa in our computational experiments.Comment: 40 pages, 8 figures, 21 table

Effectiveness of the Nigerian emergency management system with respect to building collapses, human stampedes and electrical power failures

One response to disaster incidents in Nigeria is to improve institutional preparedness and strengthen the capacity of the organisations involved. This requires adequate resources, improved communication and enhanced operations of the national emergency operations centre (EOC) to intensify coordination and better allocate resources. Factors affecting vulnerability to disasters such as building collapses, stampedes and blackouts, and the capacity of Nigeria’s emergency management organisations (considering resource availability, communication ability and operations of the EOC), were evaluated for the six main organisations involved in emergency response in Nigeria: National Emergency Management Agency, Federal Ministry of Health, Nigeria Police Force, Nigeria Security and Civil Defence Corps, Federal Road Safety Corps and National Hospital. Qualitative and quantitative approaches involving questionnaires and interviews were used. Poor housing and infrastructure, lack of disaster education, socio-economic challenges and institutional failures are the main factors that affect vulnerability to building collapses in Nigeria. Institutional failures, political issues and lack of disaster education affect blackouts, while socio-economic factors, institutional failures, political issues and lack of disaster education predominantly affect vulnerability to stampedes. Despite the need to have available resources, effective communications and functional EOCs, it appears that effective response and the implementation of emergency response activities in Nigeria are hindered by lack of adequate resources, lack of resource-sharing networks between federal, state and local government, lack of accountability, inadequate availability of equipment such as mobile phones and radios, and absence of communication networks such as LAN and WAN. Location and accessibility of each EOC, communication ability within the centre, and resources available to the EOC significantly influence the success or failure of operations of the EOC, which in return affects coordination, cooperation and integration among different levels of government and other organisations involved. In conclusion, there is a need for an emergency management plan that includes all elements and enhances resource availability and utilisation, effective communication, and coordination and allocation of resources to prevent, mitigate and respond rapidly to disasters

Disaster risk management of interdependent infrastructure systems for community resilience planning

This research focuses on developing methodologies to model the damage and recovery of interdependent infrastructure systems under disruptive events for community resilience planning. The overall research can be broadly divided into two parts: developing a model to simulate the post-disaster performance of interdependent infrastructure systems and developing decision frameworks to support pre-disaster risk mitigation and post-disaster recovery planning of the interdependent infrastructure systems towards higher resilience. The Dynamic Integrated Network (DIN) model is proposed in this study to simulate the performance of interdependent infrastructure systems over time following disruptive events. It can consider three different levels of interdependent relationships between different infrastructure systems: system-to-system level, system-to-facility level and facility-to-facility level. The uncertainties in some of the modeling parameters are modeled. The DIN model first assesses the inoperability of the network nodes and links over time to simulate the damage and recovery of the interdependent infrastructure facilities, and then assesses the recovery and resilience of the individual infrastructure systems and the integrated network utilizing some network performance metrics. The recovery simulation result from the proposed model is compared to two conventional models, one with no interdependency considered, and the other one with only system-level interdependencies considered. The comparison results suggest that ignoring the interdependencies between facilities in different infrastructure systems would lead to poorly informed decision making. The DIN model is validated through simulating the recovery of the interdependent power, water and cellular systems of Galveston City, Texas after Hurricane Ike (2008). Implementing strategic pre-disaster risk mitigation plan to improve the resilience of the interdependent infrastructure systems is essential for enhancing the social security and economic prosperity of a community. Majority of the existing infrastructure risk mitigation studies or projects focus on a single infrastructure system, which may not be the most efficient and effective way to mitigate the loss and enhance the overall community disaster resilience. This research proposes a risk-informed decision framework which could support the pre-disaster risk mitigation planning of several interdependent infrastructure systems. The characteristics of the Interdependent Infrastructure Risk Mitigation (IIRM) decision problem, such as objective, decision makers, constraints, etc., are clearly identified. A four-stage decision framework to solve the IIRM problem is also presented. The application of the proposed IIRM decision framework is illustrated using a case study on pre-disaster risk mitigation planning for the interdependent critical infrastructure systems in Jamaica. The outcome of the IIRM problem is useful for the decision makers to allocate limited risk mitigation budget or resources to the most critical infrastructure facilities in different systems to achieve greater community disaster resilience. Optimizing the post-disaster recovery of damaged infrastructure systems is essential to alleviate the adverse impacts of natural disasters to communities and enhance their disaster resilience. As a result of infrastructure interdependencies, the complete functional restoration of a facility in one infrastructure system relies on not only the physical recovery of itself, but also the recovery of the facilities in other systems that it depends on. This study introduces the Interdependent Infrastructure Recovery Planning (IIRP) problem, which aims at optimizing the assignment and scheduling of the repair teams for an infrastructure system with considering the repair plan of the other infrastructure systems during the post-disaster recovery phase. Key characteristics of the IIRP problem are identified and a game theory-based IIRP decision framework is presented. Two recovery time-based performance metrics are introduced and applied to evaluate the efficiency and effectiveness of the post-disaster recovery plan. The IIRP decision framework is illustrated using the interdependent power and water systems of the Centerville virtual community subjected to seismic hazard

Deep Reinforcement Learning-based Project Prioritization for Rapid Post-Disaster Recovery of Transportation Infrastructure Systems

Among various natural hazards that threaten transportation infrastructure, flooding represents a major hazard in Region 6\u27s states to roadways as it challenges their design, operation, efficiency, and safety. The catastrophic flooding disaster event generally leads to massive obstruction of traffic, direct damage to highway/bridge structures/pavement, and indirect damages to economic activities and regional communities that may cause loss of many lives. After disasters strike, reconstruction and maintenance of an enormous number of damaged transportation infrastructure systems require each DOT to take extremely expensive and long-term processes. In addition, planning and organizing post-disaster reconstruction and maintenance projects of transportation infrastructures are extremely challenging for each DOT because they entail a massive number and the broad areas of the projects with various considerable factors and multi-objective issues including social, economic, political, and technical factors. Yet, amazingly, a comprehensive, integrated, data-driven approach for organizing and prioritizing post-disaster transportation reconstruction projects remains elusive. In addition, DOTs in Region 6 still need to improve the current practice and systems to robustly identify and accurately predict the detailed factors and their impacts affecting post-disaster transportation recovery. The main objective of this proposed research is to develop a deep reinforcement learning-based project prioritization system for rapid post-disaster reconstruction and recovery of damaged transportation infrastructure systems. This project also aims to provide a means to facilitate the systematic optimization and prioritization of the post-disaster reconstruction and maintenance plan of transportation infrastructure by focusing on social, economic, and technical aspects. The outcomes from this project would help engineers and decision-makers in Region 6\u27s State DOTs optimize and sequence transportation recovery processes at a regional network level with necessary recovery factors and evaluating its long-term impacts after disasters

Production of Innovations within Farmer–Researcher Associations Applying Transdisciplinary Research Principles

Small-scale farmers in sub-Saharan West Africa depend heavily on local resources and local knowledge. Science-based knowledge is likely to aid decision-making in complex situations. In this presentation, we highlight a FiBL-coordinated research partnership between three national producer organisations and national agriculture research bodies in Mali, Burkina Faso, and Benin. The partnership seeks to compare conventional, GMObased, and organic cotton systems as regards food security and climate change

Principles and criteria for assessing urban energy resilience: A literature review

AbstractBetween 60% and 80% of global energy is consumed in urban areas and given the projected increase in world׳s urban population, this share is expected to further increase in the future. Continuity of energy supply in cities is affected by climate change and a growing array of other threats such as cyber attacks, terrorism, technical deficiencies, and market volatility. Determined efforts, acknowledging the interactions and interlinkages between energy and other sectors, are needed to avoid adverse consequences of disruption in energy supply. Resilience thinking is an approach to management of socio-ecological systems that aims to develop an integrated framework for bringing together the (often) fragmented, diverse research on disaster risk management. The literature on urban resilience is immense and still growing. This paper reviews literature related to energy resilience to develop a conceptual framework for assessing urban energy resilience, identify planning and design criteria that can be used for assessing urban energy resilience, and examine the relationship of these criteria with the underlying components of the conceptual framework. In the conceptual framework, it is proposed that in order to be resilient, urban energy system needs to be capable of “planning and preparing for”, “absorbing”, “recovering from”, and “adapting” to any adverse events that may happen in the future. Integrating these four abilities into the system would enable it to continuously address “availability”, “accessibility”, “affordability”, and “acceptability” as the four sustainability-related dimensions of energy. The paper explains different resilience principles associated with these abilities and sustainability dimensions. Also, different planning and design criteria were extracted from the literature and categorized into five themes: infrastructure; resources; land use, urban geometry and morphology; governance; and socio-demographic aspects and human behavior. Examination of the relationship of these criteria with the underlying components of the conceptual framework highlighted the complexity and multi-faceted nature of energy resilience. Exploration of the relevance of the identified criteria to climate change mitigation and adaptation revealed that most of the identified criteria can provide both mitigation and adaptation benefits