Decision Support Systems for Managing Natural Hazards

Paul Chan, Xue Liu, Menas Kafatos, and Hesham El‐AskaryChapman University

Joint US‐Egypt Workshop on Space Technology and Geoinformation  for Sustainable Development

Cairo, Egypt14‐17 June 2010

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Information flow for decision making

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System architecture

Prototypes

• Current: hurricanes, wildfires, agricultural disaster

• Other potentials: dust storms, sea level rise, droughts

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Hurricane module

Historical hurricane tracks

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Hurricane risk in Gulf Coast counties with major infrastructures

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Incorporating real‐time forecast information

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… and forecasted storm surge

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… and areas/infrastructures impacted by storm surge

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… and affected transportation routes

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Wildfire module**

Risk management

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Risk management

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Risk management

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Early detection

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Fire modeling/prediction

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Fire modeling/prediction

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Decision support tool for fighting wildfires

Continental scale atmospheric model

Fire behavior model

Regional scale atmospheric 

model

Operational concept

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Santa Barbara Wildfire Simulation(Between 14 Nov 1500 to 15 Nov 1000)

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Fire perimeter at 1500, Nov 14

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Predicted fire spread at 1 hour interval

Santa Barbara Wildfire Simulation(Between 14 Nov 1500 to 15 Nov 1000)

Recovery management

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The food/ag supply chain

Simulating the economy

Business sector transactionsamong states; calculated from data• 600 million B2B transactions• 7.5 million B2Final-user• 50 thousand international

Dairy

Grain

Fuel

IT

...

AK AL AR WI...50 states and DC132 businesssectors

Ag data• Ag Census• Ag Resource Mgmt SurveyTransportation data• Commodity flow survey• Freight Analysis FrameworkCommerce data• State Export Statistics• Economic CensusLabor data• Consumer Expenditure Survey• Employment/Income StatisticsEnergy data• Wholesale Electric Database

Simulating the impacts of a disaster event

Economic impacts: Economic loss; Unemployment

Damage estimates in a particular sector due to a disaster event12

Dairy

Grain

Fuel

IT

...

AK AL AR WI...

Downstream effects

Dairy

Grain

Fuel

IT

...

AK AL AR WI...

Upstream effects

Animals Farms Market Value Disposal Cost

Dairy 15,680 218 $20,718,611 $1,215,200

Beef 172,582 4,308 $95,570,845 $13,375,120

Hogs 1,924,972 597 $24,044,879 $39,480,469

Sheep 2,765 123 $197,781 $245,210

Goats 7,378 443 $534,960 $132,649

Total 2,115,999 5,246 $140,532,116 $54,315,999

A disaster eventScenario-basedanalysis

Information formitigation

Short-term economicimpact assessment

Long-term economicimpact assessment

Estimates of directdamages

Hours day 1 week weeks

Currentcapability

SAS-USAcapability

This approach enables speedy decision‐making inemergency management

Economic loss due to the destruction of all cloven-hoofed animals within a 10 mile zone

Cloven-hoofed animals within 10 mile quarantine zone in Duplin County, NC

Estimates of the immediate economic loss in a foot-and-mouth disease outbreak

Number of Animals Number of Farms Market Value of Animals Disposal Costs Output Generation Employment at RiskDairy 49 3 64,211 3,766 11,900 1Other Cattle 5,559 127 3,078,562 430,844 7,981,000 1Hogs 812,820 159 38,365,095 62,993,535 99,461,000 11Sheep 21 1 1,304 1,616 3,000 0Goats 244 16 15,261 18,921 40,000 0All 818,693 306 41,524,433 63,448,682 107,496,900 13

At-risk assets within quarantine zone

Estimates of the upstream and downstream economic impact of the foot‐and‐mouth disease outbreak

Market costs

Downstream impact

Upstream impact

Day 1

Day 5

Day 21

Projected spread of an FMD by transportation

Projected daily economic losses of the outbreak

Simulated impacts help management make decisions

Simulated state-to-state spread and the associated economic impacts of a foot-and-mouth disease outbreak.

North Carolina animal exports: potential transmission of FMD