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Session 17: Risk Mapping and Spatial Assessment Tools
Tuesday, 30/Aug/2016:
2:05pm - 3:35pm

Session Chair: Eric LINDQUIST, Boise State University
Room: Schwarzhorn

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Vulnerability Assessment Using Spatial Information in terms of Chemical Release Disaster

Jae Joon LEE, Hong Sic YUN, Moon Su SONG, Jung Hwan KWON

Sungkyunkwan University, Korea, Republic of (South Korea)

As the development of the domestic chemical industry is steadily increasing every year, the use of chemical substances is also increasing. But It is difficult to predict the exact frequency of the chemical accident because it occurs due to a defect of human errors and the deficiencies of equipment.

In 2015, South Korea made process to management chemical accident of offsite impact and risk assessment. But the organization disaster management have used administration boundary census statistical data for offsite risk assessment. It is difficult to assess the exact impact of accidents. Disaster manager should have used detailed census track. In this paper, Jipgaegu (300 people in 1 track) is used for assessment. Also, through data processing, this paper calculates daytime population for calculating the day time population. Research process follows bellow order

1. Setting research area and making chemical release scenario

2. Constructing spatial information in the nighttime population by using demographic data each zone normally 100m by 100m in urban area.

3. Constructing spatial information daytime population by using the number of worker and age-specific economic activity rate applicable to research area

4. Sorting the population into age and constructing response organization to set weight for finding social vulnerability area.

5. According to distance, site dependence vulnerability

6. Simulating chemical release accident and distribute 3 score to population on the level of impact to 3 area following the ALOHA program simulation.

Characteristics of social, dynamic, physical, location-dependent vulnerability were considered for the overall vulnerability assessment of population. Results of this study could provide the information that might be helpful to determine the policy for each step in prevention, preparedness, response and recovery to prepare for chemical release accidents.

A Spatial Decision Support System (SDSS) for Understanding and Reducing Long-Term Disaster Risk

Hedwig VAN DELDEN1,2, Graeme Angus RIDDELL1,2, Roel VANHOUT1, Holger Robert MAIER2, Aaron Carlo ZECCHIN2, Jeffrey Peter NEWMAN2, James DANIELL3, Graeme Clyde DANDY2

1RIKS, Netherlands, The; 2The University of Adelaide; 3Karlsruhe Institute of Technology

Pressures on urban centres are increasing, with urban land expected to triple in size globally by 2030. This, coupled with the increasing threat of climate change, poses significant challenges, but also opportunities, to governments, planners and communities. The SDSS presented looks to assist these stakeholders in making better long-term planning decisions by considering the dynamics of risk across hazard, exposure and vulnerability and taking a more holistic approach to risk management and reduction.

The SDSS for disaster risk reduction has been developed in collaboration between research institutions and State Governments across Australia and integrates multiple hazard models with a land use model. This allows for the inclusion of information regarding population, social capital and building stock to consider long term spatial and temporal dynamics of disaster risk. The integrated SDSS operates at a 100m resolution with a time-step of 1 year and can be used for exploratory modelling 20-50 years into the future. Hazards included in the SDSS include riverine flooding, coastal inundation, bushfires and earthquakes. Each is modelled on the basis of relevant physical properties of the hazard and includes the impacts of climate change on hydro-meteorological and bushfire hazard. The land use model is driven by socio-economic developments, and allocates land use activities throughout the region of interest.

The SDSS can be used to explore the impact of risk reduction options, such as levees, prescribed burns, building hardening, land-use planning, and education/ awareness programs. The options can be assessed through SDSS-calculated risk reduction, environmental and social indicators, along with a cost-benefit-analysis. The SDSS has an easy-to-use Graphical User Interface, allowing stakeholders to explore long-term risk and the impacts of policies. This can allow for cities to be designed in terms of strategically minimising risk by considering its citizens’ and buildings’ vulnerabilities, and their exposure to a changing hazard.

Tools for Assessment and Mapping of Natural Hazard Risks

Michael BRÜNDL, Linda ZAUGG

WSL Institute for Snow and Avalanche Research SLF, Switzerland

In the past ten years, the assessment of risk has become a key element in decision-making for natural hazards and other societal areas. Risk – technically defined as the product of hazard, vulnerability and objects at risk – is one criterion in cost-benefit-analyses conducted to optimize the allocation of public money. Although risk assessment is common practice among professionals in most European countries and worldwide, the market for calculation and mapping tools is rather sparse.

We address this issue by presenting two applications recently developed in Switzerland. Firstly, we present the software EconoMe-Develop (, which was developed for single or multi-risk assessment primarily for gravitational processes such as snow avalanches or floods. Due to its flexibility, it can also be used for assessment of meteorological risks or earthquakes. Secondly, we present RAMMS::RISK, which was developed as a risk calculation and mapping tool for mountain natural hazards, such as avalanches, debris flows and rockfalls. RAMMS::RISK is independent of commercial GIS products and was conceptualized as a module of RAMMS, a numerical model for simulating snow avalanches, debris flows and rockfall events in three-dimensional terrain.

We will illustrate the application of both tools with case studies, and highlight how both applications can support decision makers in their daily work.

Risk Assessment and Mapping of Harmful Algal Bloom in Farming Fisheries of South Sea (Korea)

Moonsoo SONG1, Hongsic YOON1,2, Taewoo KIM2, Jaejoon LEE1

1Interdisciplinary Program in Crisis Disaster and Risk Management, Sungkyunkwan University; 2Department of Civil and Environmental Engineering , Sungkyunkwan University

Recently, in connection with the climate change, Harmful Algal Bloom (HAB) with the excessively high amount of microorganisms and various substances that they produce cause serious problems in the farming fisheries. Large amounts of toxicity and slime of hazardous algae make lower dissolved oxygen in the seawater and reduce the capacity of oxygen exchange of fish by sticking to the gills. It kills by suffocation marine creatures and gives massive damage to aquaculture.

In this study, the HAB monitoring technology using the images of the Geostationary Ocean Color Imager (GOCI) and a risk assessment was performed about the damages of aquaculture farms due to the HABs in the southern coast of South Korea. To identify Cochlodinium polykrikoides-red tide from non-red tide water (satellite high chlorophyll waters), use improved spectral classification method proposed by Son et al.(2011) for the GOCI. This modified spectral classification method for GOCI led to increase accuracy for C. polykrikoides and non-red tide blooms and provided a more reliable and robust identification of red tides over a wide range of oceanic environments than was possible using chlorophyll-a concentration, or proposed red tide detection algorithms. Once the area of HAB was classified from GOCI image, the spatial distribution of the red tide area was presented on the ArcGIS 10.1. Then, a risk assessment was conducted with the attribute data of aquaculture farms through the GIS database. Finally, minimization of damages to aquaculture farms from red tides and the minimization of the spread of red tide damages.

Dynamic Risk Map (DRM) for Enhancing Risk Assessment of Construction Projects in Random Districts in Egypt.

Nael Yousry ZABEL1,2, Ghadeer Rashed ALFANDI3, Mohamed El Said SALEH4

1WorleyParsons Engineering Consultancies, Saudi Arabia; 2Institutie of Higher Engineering & Technology – Fifth Assembly, New Cairo, Egypt; 3Civil Engineering Department, College of Engineering, Design, and Physical Science, Brunel University London, Uxbridge, UK; 4Department of Civil Engineering, Military Technical College, Cairo, Egypt.

The Government of Egypt is facing a tremendous challenge to overcome the threats of the dilemma. Managing the risk factors in upgrading infrastructure projects in the slum is a critical dimension of the dilemma in Egypt, One approach to overcome this hardship is to provide a facility to understand and visualize such dependencies which is risk mapping. This paper presents the implementation of powerful tool called Dynamic Risk Map (DRM). Thus enhancing risk prediction of a dynamic risk assessment. DRM consists of all potential dependency relationships between pairs of risk factors in same risk group or in two different risk groups. From DRM it is possible to evaluate the risk significance in unlimited project scenarios that enabling the decision maker for more wide vision for his decision. This paper proposes a method of presenting in a visual fashion the risk factors that have a bearing on construction projects in random districts failure and their interrelationships. This allows the different parties in a project to use the diagram to collaborate in the creation of risk models. Further analytical capabilities of such a diagram will even improve our understanding of the magnitude of project risks on its outcomes.

Development of Urban Flood Analysis Model for Real-time Urban Flood Forecasting and Modeling

Sengyong CHOI1, Jaewoong CHO1, Yuntae KIM1, Seongyeol CHOI2

1National Disaster Management Research Institute, Ministry of Public Safety and Security, Republic of Korea; 2Disaster Prevention and Safety Institute, Republic of Korea

In order to prepare and response for the flooding damage in an urban area due to abnormal climate and disaster circumstance changes, the integrated inundation prediction model, which is dependent on the complicated drainage systems of an urban area, is necessary to forecast and warn about inundation. The purpose of this study is to develop inundation prediction model that interlinking ground and rain water pipe network space in an urban area. Especially the model was developed in consideration of factors such as the buildings, roads, grate inlets, and underground that affect the flow in an urban areas. In order to verify the applicability of the developed model it was applied to a pilot for different urban areas and rainfall events. In addition, a comparative analysis was carried out with the existing model to verify the accuracy of the developed model. As a result of the comparison, the developed model was more accurate than the existing model and had higher availability. The developed model in this study can be utilized to build real-time urban flood forecasting and warning system in the future.

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