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

W3-C
Atlas Shrugged: Geospatial Decision Analysis

Room: Salon C   1:30 pm–3:00 pm

Chair(s): Michelle Hamilton   mhamilton@ccri.com

Sponsored by Decision Analysis and Risk Specialty Group



W3-C.2  1:50 pm  Integrating Geospatial Information in Network Modeling for Prepositioning Supplies under Extreme-event Conditions. Resurreccion JZ*, Blanco AB, Santos JR, Bangate JM; University of the Philippines-Diliman; The George Washington University   joannazr@gwu.edu

Abstract: In the most disaster-prone countries such as the Philippines, extreme-weather events including typhoons bring devastation to infrastructure and disruption to various industrial, agricultural and service sectors of an economic region. Moreover, these events place the health and safety of affected communities, particularly in rural areas, at greater risk. With intensified threats of climate change, there is a rising complexity in mitigating this risk. Furthermore, stringent response time requirements become primarily inherent in the early stages of today’s disaster relief operations. Consequently, pre-positioning of supplies has been found to largely contribute in the mitigation of disaster consequences by reducing response time, casualties and operational costs. In this regard, this research explores the utilization of flood hazard map information in network analysis for pre-positioning relief supplies under potential destruction of pre-positioned supplies and capacitated-supply points. A model is developed to integrate the spatial dimension in evaluating the associated vulnerability of supply point based on local path flood susceptibility. The research will demonstrate the method through an adaptation of the Light Detection and Ranging or LIDAR-based 3D flood hazard map data developed by the Philippine government agencies in collaboration with various research institutions to derive path flood susceptibility. Start times of pre-positioning activities and restocking requirements are derived based on the typhoon return period classification and size of exposed population. The model determines the supply points to preposition supply to, preposition quantity and corresponding path options. The resulting model will have flexibility and scalability over flood hazard maps of different return periods and different regions.

W3-C.3  2:10 pm  Geospatial Decision Analysis for Military Base Camp Siting. Cegan JC*; US Army Corps of Engineers   jeffrey.c.cegan@usace.army.mil

Abstract: The US Army is in need of the ability to rapidly plan and site base camps in order to maximize the combat effectiveness of deployed forces. By defining mission specific site requirements prior to the deployment and construction or base camps, commanders and planners are able to optimize base camp site selection and design. Currently, existing doctrine and guidance for contingency basing (CB) are not developed to support deployment in dense urban environments. Without this doctrine, the U.S. military falters when deployment is desirable or necessary in a dense urban environment. Preliminary research reveals the inadequacy of current doctrine for conducting operations in such an environment (Chief of Staff of the Army, 2013). The CB-SITE project seeks to address these problems by developing a comprehensive tool for base camp site suitability assessment. CB-SITE progress includes (1) interviewing a dozen current and former US Army personnel with active duty contingency basing experience (2) analyzing a dozen documents describing existing US Army policy and recommended good practice, (3) developing a preliminary set of spatial criteria (i.e., standards that influence CB siting), and (4) developing a preliminary framework set of design choices, i.e., factors that will influence how criteria are interpreted. As a screening tool, CB-SITE will assist with optimal selections of promising locations for detailed investigation through the use of multi-criteria decision analysis. The tool will guide users on factors that require consideration during site selection and help avoid unintended consequences following site placement.

W3-C.4  2:30 pm  A Regional Risk and Vulnerability Assessment with Multiple Criteria Decision Analysis to Support Evidence-Based Investment. Hamilton M*, Morath D, Curran R, Hughey E, Green J, Batzel J; CCRi   mhamilton@ccri.com

Abstract: The aim of this research is to inform the investment of humanitarian assistance projects to build more resilient regions. The first part of this research is to conduct a multi-year regional Risk and Vulnerability Assessment (RVA). The RVA provides a risk profile for the region along with drivers of risk within individual countries, thereby identifying areas in need of investment. 51 indicators are used to assess three main components of risk: hazard exposure, vulnerability and coping capacity. Hazard exposure measures the historical population and economic exposure to multiple hazards. The vulnerability component measures the characteristics and circumstances of a community, system or asset that make it susceptible to the damaging effects of a hazard. The coping capacity component measures the ability of people, organizations and systems, using available skills and resources, to face and manage adverse conditions, emergencies or disasters. The second part of this research uses multi-criteria decision analysis to help potential humanitarian assistance investors to prioritize investment based on their mission for addressing needs. The approach defines multiple factors for investments by aligning the RVA indicators with stakeholder mission areas which include: governance and rule of law; economic stability; transportation & communication infrastructure; public health; public welfare; education & information; and environmental stability. Given stakeholder priorities and limited resources, some of these factors may be more suitable for investment than others. Analytic hierarchy process is used to elicit stakeholder preferences for the seven factors for investment. Given the factor weights and the indicator scores for each country, the result is a ranked prioritization of countries for investment. The method is demonstrated in the 10 ASEAN countries of Brunei Darussalam, Cambodia, Indonesia, Lao PDR, Malaysia, Myanmar, the Philippines, Singapore, Thailand, and Viet Nam.



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