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Practical applications of hazard maps for Planning, preparedness, response and risk communication Wei-Sen Li Secretary General, NCDR, Chinese Taipei Co-Chair, APEC Emergency Preparedness Working Group 2015/05/04, Lima, Peru Workshop on
2015/05/04, Lima, Peru
Wei-Sen Li
Secretary General, NCDR, Chinese Taipei Co-Chair, APEC Emergency Preparedness Working Group
Workshop on Promoting disaster risk management and hazard mapping to better understand potential risks to the supply chain
Planning, preparedness, response and risk communication
Key elements, applications and Sendai Framework for Disaster Risk Reduction
A sample of data process for information intelligence
7 practical applications including typhoons, debris flow, landslides, floods, evacuation, hazard maps and community-based disaster risk management
Dynamic information coverage Embraces open data and big data
On text book, only one answer For a solution, like hazard maps,
Data Organizing Data Analyzing Data warehousing Data Presenting “Extract”, “Transform” and “Load”
Physical vulnerabilities Social vulnerabilities Mystical events Numerical models Observations
Print-outs Sign boards Web-based GIS Official sites or social media Any limitation to use
Governments Research institutes NGOs, NPOs Media, social media Citizens
Risk communication at communities Easily understandable
To tell routes, shelters and risk potential Clearly to take actions
Decision making, common operating picture Integrated products
To be reference of insurance or risk identification Prepare for multiple hazards
To control risks Sustainability
To protect employees, estates and profits Private sector’s involvement
To set up scenarios with different levels of risk Connect all stakeholders
To enhance resilience, preparedness, responses and recovery Before, during and after a disaster
01 01 02 02 03 03 04 04
Strengthening disaster risk governance to manage disaster risk Enhancing disaster preparedness for effective response and “Build Back Better” Understanding disaster risk Investing in disaster risk reduction for resilience
Key elements, applications and Sendai Framework for Disaster Risk Reduction
A sample of data process for information intelligence
7 practical applications including typhoons, debris flow, landslides, floods, evacuation, hazard maps and community-based disaster risk management
Dynamic information coverage Embraces open data and big data
Too much or too little information during emergency response
Why making use of data and information is critical – observations from Typhoon Marokot since 2009
Lack of common operating picture to coordinate actions
When and how to make timely decisions
Combine more than 20 units, 120 maps （Big Data） Apply – Provide situation assessment system
Weather
Flood
Geo
2013年蘇力颱風
Value-added – Provide early warning information
Action-based Multiple hazards Refining data sets Trans-agency Sharing Dynamically evolving Interpreting Presenting
Information flows and synergy for typhoon emergency operation
Key elements, applications and Sendai Framework for Disaster Risk Reduction
A sample of data process for information intelligence
10 practical applications including typhoons, debris flow, landslides, floods, evacuation, hazard maps and community-based disaster risk management
Dynamic information coverage Embraces open data and big data
Typhoon Forecast Rainfall Forecast Flood Simulation
Yi-lan City
The land use Categories of inundation area Rapid Computing
Suao Township
養殖. 農業 住宅. 農業 農業. 林地
Impact Assessment Suggestions
宜蘭市 蘇澳鎮 頭城鎮
The early warning Process for the disasters assessment
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Three principles to integrate information for typhoon emergency operation
Scenario-based description for deployment and response in advance Cross-cutting information exchange to monitor evolving situations
Estimate potential risk of landslide 2014, 07/23 06：00 am
Graph and table plus GIS to show spatial and time- dependent factors
High Risk
Demands and supports of S&T according to emergency operation stages
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Application 1: Water Resources Agency
– Flood Warning
Latest 24hr (200mm/24hr)
Yilan County: Warning areas
Toucheng Jiaoxi Zhuangwei Yuanshan Yilan City Wujie Sanxin Luodong Dongshan Suao
Major flooded areas
Estimated floods in 24hrs based on forecast issued by CBW
Toucheng
Jiaoxi Yilan City Wujie
Luodong Dongshan
Suao Sanxin
Yuanshan
Flood Depth
0.3-1.0 m 1.0-2.0 m 2.0-3.0 m > 3.0 m 0.5-1.0
15 Warning
Yilan County
Disclosed info: time, locations and scientific scenario
7/11 0:00 7/11 6:00 7/11 12:00 7/11 18:00 7/12 0:00 7/12 6:00 7/12 12:00 7/12 18:00 7/13 0:00 7/13 6:00 7/13 12:00 7/13 18:00 7/14 0:00
Time
10 20 30 40 50 60 70 80
小時雨量強度(mm/hr)
100 200 300 400 500 600
有效累積雨量(mm)
7/11 8:30 Typhoon sea warning 7/11 20:30 Typhoon land warning
Date and Time Forecasts or observations of rain Warning on debris flow 7/12 14:00 24hr forecast on rain, 500-800mm Issue Yell Alert 7/12 20:00 Observation< 50mm Keep Yellow Alert 7/12 23:00 Observation reached 110mm Keep Yellow Alert 7/13 03:00 Observation > 300mm Issue Red Alert
17 hours 13 hours
Issuing Yellow Alert
尖石鄉警戒值 Threshold of action: 300 mm Yellow: Evacuation Preparation Red: Evacuation
Application 2: Soil and Water Conservation Bureau –
Warning on debris flow
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Issuing Red Alert
Rainfall accumulation Rainfall intensity
Disclosed info: time, locations and scientific scenario
Application 3: Evidence-based emergency operation – Early evacuation Typhoon Kong-Rey in 2013
Potential Risk Map of debris flow at township level Scientific evidence to carry out early evacuation
Threshold value
200 mm accumulated rainfall in 24hrs Forecast of rainfall Intensity of rainfall
Critical point at midnight Red alert
The best period of time to evacuate residents Evidence-based emergency operation – Early evacuation Typhoon Kong-Rey in 2013
Case of successful early evacuation during Typhoon Fanapi , in Lai-Yi village, Sep. 2010
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照片來源：水保局
9/18 05:30 9/19 08:40 14:00 15:00 23:00
Issue land warning Early warning Evacuation
Typhoon landfall time Landside in Lai-Yi
1. Buried house: 50 2. Causality: 0
32 hours ahead
2009 after Typhoon Morakot
Progressive Improvements for Typhoons in Chinese Taipei
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Typhoon Max.Intensity (mm/hr) Accumulated Rainfall (mm) Evacuation (Person) Ceased or Missing (Person) 2001.07.28 Toraji 147 757
2001.09.17 Nari 142 1,462 24,000 104 2004.06.30 Mindulle 167 2,005 9,500 41 2005.07.18 Haitang 177 2,124 1,208 15 2005.09.01 Talim 119 766 1207 6 2005.10.02 LongWang 154 776 945 2 2006.07.12 Bilis 95 1,013 409 3 2007.08.16 Sepat 122 1,399 2,531 1 2008.07.16 Kalmaegi 161 1,027 179 26 2008.07.28 Fung-Wong 121 830 1,303 2 2008.09.10 Sinlaku 97 1,608 1,987 22 2008.09.27 Jangmi 85 1,137 3,361 4 2009.08.07 Morakot 100 2,965 24,775 695 2010.09.19 Fanapi 125 1,128 16,568 2 2010.10.21 Megi 183 1,195 3,453 38
Compound Disaster Extreme weather Compound Disaster Compound Disaster Compound Disaster
NCDR Joined EOC
發生4級有感地震
Screening high risk highways based on hourly rainfall data
Sorting sensitive slopes If risk reaches level B, send alert Monitoring riks
“台21線那瑪夏 210k”路段現”紅 色”強降雨,該路 段屬”A”級邊坡, 最近一次致災記 錄係”102潭美颱 風便橋沖毀”
Alert
Application 4: Directorate General of Highways – Automation on monitoring risk highways
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Stage 1 Risk identification Stage 2 Alert dispatch
Flood Flood high risk area
Application 5: NCDR
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Geo
Slope land risk analysis Geo Road closure analysis Disaster impact and suggestion Disaster preparedness focus
羌黃坑
Tribe: Tonglin area scale: over 60 houses slip layer: No beneath slope land edge: Yes 郡坑活動中心
Weather
Flood
Geo
Application 6: Massive Gas Explosions in Kaohsiung, Aug 1st, 2014
Direct Impact and Loss
Affected area: 2~3 km2 Destroyed street: 14 km 32 dead, 321 injured
Causes
Propane leaking from a rusty petrochemical pipe to the sewer system and explode
AP Photo
To identify suspensions of public services emergency water supply station and affected area
Range of affected area Emergency water supply station Power supply suspension
Required data for geo- spatial construction
Street maps
Pipeline system: petrochemical material, tap water, natural gas, power, telecommunications and drainage
Locations explosion with time factors
Aerial images of Prior-and post- explosion
Locations of shelters
Affected areas
Time frame of recovery work
Data sources: central and local governments, industrial sector and crowd sourcing
Thought functions of CCTV to monitor the affected site
Application of CCTV
Original purposes
Observations of flash flood, road closure, water levels, reservoir
For monitoring gas explosion
Traffic volume, traffic control, progress of recovery and etc. Locations of explosion with time
factors
Central and local governments, industrial sector and crowd sourcing Next phase
To include all IP CCTV in urban areas
1,159 hazard maps were produced since 2010
Application 7: Produce Hazard map for flood and slopeland disasters
Chinese Taipei-wide scale County-wide scale Township scale
Casualties cause by collapsed buildings Simulated EQ Landslides Liquefaction System failures Power supply Water supply Transportation
Application 8: Scenario-based analysis for urban area by grid method
Application for Large-scale earthquake
Using big data to develop information-based preparedness and scenarios on earthquakes
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Application for Large-scale earthquake
Digitalized Population Density Distribution: stationary and dynamic characteristics
Mesh size: 500m X 500m Floor areas of buildings Population Distribution, 2010 Proportioned Population Distribution Population distribution proportional to flood area at night
Taipei City Keelung City New Taipei City
Coverage: Taipei City, New Taipei City and Keelung City Grid size: 1.0 km x 1.0 km (2,388 grids in total) Population (by August, 2014) Taipei City: 2,695,007 New Taipei City: 3,959,855 Keelung City: 373,721 Data sampling 9 am, 3 pm and 9 pm Not receiving data in real-time mode
Data mesh and data sampling Big data produced by the Chunghwa Telecom
7 M Application for Large-scale earthquake
Averaged data at 9 am Averaged data at 3 pm Averaged data at 9 pm Application for Large-scale earthquake
Differences at weekdays, weekend and holidays Land use affects population distribution Long-term observation required During weekdays, inflow from neighborhood cities
Application: To analyze factors affecting population distribution
Application for Large-scale earthquake
Application 9: Key elements to build up disaster-resilient community
32
Mature and reliable knowledge Monitoring and early warning Risk and vulnerability assessment Preparedness plan
》曾經發生的災害類型與地點 》過去災害發生時影響的範圍 》未來可能發生災害的地點 》社區的重要設施( 學校) 》社區的災害弱勢民眾 》緊急避難場所 》自然環境( 野溪) 》公共工程 ( 擋土牆) 》社區環境照片 》易致災因子
mapping
field survey Relevant resource environmental & social vulnerability Past disasters
Mapping community vulnerability
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Operational Model partnership with NGOs
34
36
Assessment Training Scenario-based drill Group Discussion
Community-level hazard map for a indigenous tribe after Typhoon Morakot
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Hsinchu Science Park
Tongluo Jhunan Biomedical Park Longtan Central Science Park Yunlin Kaohsiung Southern Science Park Since 1980 Since 2003 Since 1996 Yilan Biotechnology,
Telecommunications Opto-Electronics Defense technology Industry Precision Machinery Panel Industry
Holi
Agricultural Biotechnology Semiconductor, Panel Industry IC,Opto-Electronics elecommunication Biotechnology Semiconductor,, PC/Peripherals, Telecom, Opto-Electronics, Machinery Biotechnology Telecommunications, Knowledge service
3 Core Parks + 8 Satellite Parks Total 11 Science Parks
Opto-Electronics
Application 10: Briefing of Science Parks in Chinese Taipei Business Continuity Plan
Economic Contributions by Science Parks
26.9% (2010)
ICT is the engine
economy
second highest in history
In 2012, growth rate in all science parks is 5.2%
Estimates for 2013
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Potential Risks to Science Parks
Floods
To block the logistics support; To endanger workers’ safety Flood maps
Droughts
To slow IC producing process Long-term forecast based on climate change
Landslides
To interrupt electricity supply Risk maps
Earthquakes
To cause facility damages Risk map
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Basic Flood Maps for Science Park
Scenario: 600 mm rain in 24 hours
2011/12
2013/01 2013/02
Risk of Drought
Above historical avg. Below historical avg. Below historical avg.
Threat of Typhoons
P P S S P P P S S P P
Hsinchu Central Southern
north and central areas, especially north.
Path1 Path 2 Path 3 Path 6
Trend Analysis of Typhoons under Climate Change
Key elements, applications and Sendai Framework for Disaster Risk Reduction
A sample of data process for information intelligence
7 practical applications including typhoons, debris flow, landslides, floods, evacuation, hazard maps and community-based disaster risk management
Dynamic information coverage Embraces open data and big data
Supports by science and technology are key to succeeding disaster risk reduction
Scientific Prediction Real-time Monitoring In-time Operation
based on models
deployment
decision support
technology development
data based on gauges
blind areas by forecast
revising decision support
location, transmission
based on well- defined plan
time before it’s too late
allocating emergency support
determination of all- leve administrators
Synergy between public and private sector on alert dissemination
Business, App developers and industry are welcome to receive and use the open information
Typhoon, Torrential rain
Earthquake, Tsunami Debris flow
Reservoir discharge, flood, water level rise Closure or interrupt
Operation suspension
Operation suspension
Classes canceled
Alerts Disaster Information Open Data Platform
Server Receive
CAP check process
ATOM service PUSH service
Web alert unit
Open exchange platform Social media sharing
“big data” “open and actionable”
Information to the general public – collaboration with Google’s services
apply for interfacing alert data
Google Crisis Map Google Alerts
Make “Big data” “open and actionable”
the major challenges to overcome
relationship for integration
could hamper decision making
information or maps by request
rules and synergy to focus real issues
Conclusions and future challenges
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Business resilience Emergency Response Travel Facilitation Global Supply Chain Resilience Application of Open data and Big data to Emergency Preparedness Critical Infrastructure Security and Resilience APEC Contributions Hyogo Framework for Action 2 (2015) Private sector’s involvement
EPWG (2015) EPWG, SCCP, BMG (2013) TPTWG(2012) SMEWG (2011) CTWG (2014)
Build up linkages among APEC on emergency preparedness. Leverage resources by planned actions. Share the best practices and information. Promote public- private partnership. Encourage cross- fora workshops on disaster resilience GDACS Information input
Wei-Sen Li E-mail: li.weisen@ncdr.nat.gov.tw