Society For Risk Analysis Annual Meeting 2017

Session Schedule & Abstracts


* Disclaimer: All presentations represent the views of the authors, and not the organizations that support their research. Please apply the standard disclaimer that any opinions, findings, and conclusions or recommendations in abstracts, posters, and presentations at the meeting are those of the authors and do not necessarily reflect the views of any other organization or agency. Meeting attendees and authors should be aware that this disclaimer is intended to apply to all abstracts contained in this document. Authors who wish to emphasize this disclaimer should do so in their presentation or poster. In an effort to make the abstracts as concise as possible and easy for meeting participants to read, the abstracts have been formatted such that they exclude references to papers, affiliations, and/or funding sources. Authors who wish to provide attendees with this information should do so in their presentation or poster.

Common abbreviations

T4-C
Symposium: GIS-Aided Decision Tools for Managing Environmental Risks and Disasters

Room: Salon C   3:30 pm–5:10 pm

Chair(s): Sheree Pagsuyoin   Sheree_Pagsuyoin@uml.edu

Sponsored by Decision Analysis and Risk Specialty Group

This session focuses on the assessment, mitigation, and monitoring of environmental risks and disasters, with emphasis on water and health. Presentations will highlight the implementation of GIS-aided decision tools for risks management that are of value to environmental risks managers, planners, and policymakers.



T4-C.1  3:30 pm  Workforce, Economy, Infrastructure, Geography, Hierarchy, and Time (WEIGHT): Reflections on the Plural Dimensions of Disaster Resilience. Santos JR*, Yip C, Pagsuyoin S, Thekdi S; George Washington University   joost@gwu.edu

Abstract: The concept of resilience and its relevance to disaster risk management has increasingly gained attention in recent years. Indeed, efforts to enhance the resilience of vulnerable systems against disruptive events have been shown to generate significant benefits in terms of reducing the associated losses and expediting the recovery timeline. In this paper, we explore the complexity and plurality of disaster resilience. In particular, we propose a conceptual framework that decomposes resilience into six primary dimensions: workforce, economy, infrastructure, geography, hierarchy, and time (WEIGHT). These dimensions are not addressed holistically in the literature; often they are either modeled independently or in piecemeal combinations. This paper provides a review of each dimension and provides insights for enhancing disaster risk management through the recognition and coordination of the multiple dimensions of resilience. Through this paper, we also aim to spark discussions among researchers and policymakers to develop an integrated framework for evaluating the efficacy of resilience strategies; for example, the proposed dimensions can be treated as multiple objectives in the context of disaster risk management and decisionmaking. Furthermore, the WEIGHT dimensions may also be used in developing a structured approach that can potentially generate new approaches for data analytics of resilience-related information and knowledge bases.

T4-C.2  3:50 pm   Risk-based decisions and strategies for geospatial multi-network resilience. Thekdi S*, Aros-Vera F; University of Richmond   sthekdi@richmond.edu

Abstract: Recent high-profile disasters have caused catastrophic disruptions to networks responsible for efficient movement of people, goods, services, and information. Deficiencies in coordination among regions and unbalanced resilience characteristics have exacerbated these disruptions. We address these issues by creating models for: 1) Developing a geospatial data-informed multi-network resilience model that expands beyond traditional boundaries, 2) Assessing the most critical nodes of the multi-network using a variety of network uses, such as highway freight movement, mixed-use commuting, waterway freight movement, and others, 3) Developing a simulation and decision-support model to understand priorities for disruptive scenarios that are considered to be of low-probability and high consequence, such as environmental disasters, cyber-terrorism, and energy grid failures. This paper is the first to support decision-making for data-informed risk mitigation strategies for multi-networks with unbalanced resilience characteristics. The methodology will be applied to a case study for the Great Lakes mega-region, consisting of 38 cities, with maritime uses responsible for over 200 million tons of cargo annually, local economies critical for large-scale manufacturing and agricultural uses, and with a population of over 60 million.

T4-C.3  4:10 pm  Ecological Risk Assessment of Heavy Metals in Soil, Water and River Sediments in and around Bued River. Diola MBLD, Resurreccion AC*, Bautista CC, Quiocho RE; University of the Philippines Diliman   acresurreccion@up.edu.ph

Abstract: Heavy metals in the environment may cause harmful effects not only to humans but also to ecological receptors. This study performs an ecological risk assessment at a small scale mining community in Camp 6, Tuba, Benguet, Philippines as part of the Mineral Extraction for Sustainability and Responsibility (MiNERS Project) following the Ecological Risk Assessment Framework established by the United States Environmental Protection Agency (US EPA). This study aims to quantitatively measure risk to non-human receptors due to possible exposure to lead and arsenic in and around Bued River in Benguet, Philippines. Arsenic and lead in soil were detected and observed to range from 3.22-50.72 mg/kg and 50.68-641.21 mg/kg, respectively. Average bioconcentration of arsenic and lead to plants were calculated to be 0.085474 and 0.001472, respectively. Chronic and Acute Hazard Quotients and Hazard Indexes of media receptors were also calculated with exposure variables set to media concentration of the dwelling. Similarly, mentioned parameters were also calculated for terrestrial receptors. Based on the Hazard Quotients and Hazard Indexes, it was found that media receptors will likely to have Moderate Impact affecting sensitive and standard species whereas terrestrial receptors will probably experience Negligible Impact concerning only sensitive species.A spatial analysis was also performed using the Ecological Risk Assessment software Spatial Analysis and Decision Assistance (SADA). With the use of SADA software, contoured ecological dosage maps for broilers and laying fowls are produced. The maps cover all five points where vegetation and soil samples were collected, providing a more graphic illustration for the distribution of intake of receptors with respect to space.

T4-C.4  4:30 pm  Spatio-Temporal Drought Risk Analysis Using GIS-based Input Output Modeling. Pagsuyoin SA*, Santos JR, Salcedo G, Yip C; University of Massachusetts Lowell   Sheree_Pagsuyoin@uml.edu

Abstract: A significant number of studies on climate change have predicted an increase in the frequency and severity of droughts across the globe. Some of these predictions are already felt; for example, northeastern United States has recently experienced record rainfall deficits, triggering government agencies to issue warning-level to emergency-level drought advisories in the region. Since water is an essential resource in producing goods and services, droughts lead to economic losses that propagate through the interconnected sectors of an economy. Further, these sectors exhibit varying resilience to drought severity and duration depending on their reliance on water availability. In the present work, we develop a spatial and dynamic input-output (IO) modeling framework to examine the adverse effects of drought events on interdependent economic sectors. A decision support system utilizing geographic information systems (GIS) was created to: (1) model the progression of drought intensity, (2) simulate the dynamic behavior of economic sectors during the drought timeline and throughout the various phases of recovery, and (3) assess the regional impacts of these behaviors on the regional economy. The resulting integrated IO-GIS model was applied to the State of Massachusetts, which experienced historic widespread drought conditions in 2016.

T4-C.5  4:50 pm  Using GIS data and tools to assess the vulnerability of industrial facilities and natural resources to flooding events. Mayo MJ*, Ikeda S, Briggs NL, Petito Boyce C, Mayfield DB; Gradient   mmayo@gradientcorp.com

Abstract: Because of changes in the Earth's climate, the number and intensity of flooding events is predicted to be greater in the future. A higher frequency of major flooding events could increase risks to human activities and structures (e.g., industrial facilities) as well as natural resource areas located near water bodies. Vulnerability assessments are a common first step in risk mitigation planning, and can help identify potential flooding impacts on infrastructure, human health, and the environment. We present a screening-level approach using publicly available geospatial data and Geographic Information System (GIS)-based tools for assessing industrial facility vulnerability and potential damages to natural resources due to flooding. Our approach demonstrates that key information – such as Toxics Release Inventory data, US Environmental Protection Agency hazardous waste site and Discharge Monitoring Report facility data, the National Wetlands Inventory, the National Land Cover Database, FEMA floodplain data, NOAA hurricane storm surge hazard data, and geospatial information for recent flood events – can be combined within a GIS database to yield a robust dataset for conducting a screening-level vulnerability assessment. We illustrate this approach for two US case study areas, located along the central Mississippi River and the southeast US coast. Our discussion focuses on the potential for direct flooding damage to infrastructure and natural resource areas, and the potential impacts associated with pollutant mobilization, both of which could result in regulatory action or litigation. We show that performing GIS-based flood vulnerability assessments can identify facilities and areas at risk, delineate pre-event baseline conditions, and inform risk mitigation planning.



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