**6. Conclusion**

Combining quantitative fire effects analysis with burn probability and intensity maps allows for a quantitative, actuarial representation of risk in a spatial context. Risk assessment can inform the spectrum of wildfire management activities, from real-time management of incidents to proactive fuels management to reduce losses from future fires. Comparative risk assessment enables the exploration of tradeoffs across alternative investments in prevention, fuels management, and suppression response capacity, and ideally will lead to improved efficiency in pre-suppression and suppression planning. The framework we promoted here aligns with previously established ecological risk assessment frameworks, and is increasingly being adopted for federal wildfire management in the United States. The framework can be consistently applied across planning scales, is objective, repeatable, probabilistic, and spatially-explicit. A great strength is the flexibility of the framework, in that analysts can adopt alternative approaches to characterize wildfire hazard, to characterize fire effects and response functions, and further to use alternative weighting schemes to integrate risk calculations across HVRAs. A further strength is the scalability of the framework, which can be applied from project-level planning to strategic, nation-wide analysis.

Despite the strengths of this approach there remain limitations and challenges to address. Understanding current risk is not the same as projecting future risk, which requires prediction of changes in vegetation from natural growth and from other disturbances, changes in demographics and development patterns that could expose more human communities to wildfire risk, the dynamic feedbacks of wildfires changing landscape conditions, and the influences on fire regimes of a changing climate. Characterizing risk is a necessary but not sufficient component to developing, selecting, and implementing mitigation strategies. Information about management opportunities, treatment costs, and their relation to risk factors needs to be considered, as does uncertainty related to science delivery and policy direction.

A number of promising extensions to the work presented in this chapter exist. Embedding geospatial wildfire risk analysis within optimization algorithms could inform multiple applications, for instance pre-positioning aerial firefighting resources, initial attack home base locations and dispatch strategies, fuels and vegetation management, and incident management. Fuel management in particular is a promising avenue for spatially explicit optimization approaches. Increasing use of expert systems plus appropriate fire effects models will enable improved estimates of the consequences of wildfire. Increasing use of multi-criteria decision analysis techniques will enable integrated assessments of risk across social and ecological values, and will facilitate prioritization efforts. Non-market valuation studies could further assist prioritization efforts and articulation of management tradeoffs. One very important, and highly uncertain, topic is the consideration of future wildfire risk as a function of contemporary management, land use patterns, vegetative succession and disturbance, and, importantly, climate change.

#### **7. Acknowledgement**

The authors wish to recognize and thank Julie Gilbertson-Day, Mark Cochrane, Anne Birkholz, Jon Rieck, Joe Scott, and Don Helmbrecht for various contributions to figures and tables presented in this figure. The lead author is grateful for support of the Rocky Mountain Research Station and the National Fire Decision Support Center.

#### **8. References**

116 Novel Approaches and Their Applications in Risk Assessment

be applied at project-level to regional to national analyses. A number of improvements can and are being pursued, such as refining the fire simulation outputs, identifying a larger and more representative set of HVRAs, introducing more structure and engaging more experts to define response functions, and using more complex multi-criteria decision analysis

Combining quantitative fire effects analysis with burn probability and intensity maps allows for a quantitative, actuarial representation of risk in a spatial context. Risk assessment can inform the spectrum of wildfire management activities, from real-time management of incidents to proactive fuels management to reduce losses from future fires. Comparative risk assessment enables the exploration of tradeoffs across alternative investments in prevention, fuels management, and suppression response capacity, and ideally will lead to improved efficiency in pre-suppression and suppression planning. The framework we promoted here aligns with previously established ecological risk assessment frameworks, and is increasingly being adopted for federal wildfire management in the United States. The framework can be consistently applied across planning scales, is objective, repeatable, probabilistic, and spatially-explicit. A great strength is the flexibility of the framework, in that analysts can adopt alternative approaches to characterize wildfire hazard, to characterize fire effects and response functions, and further to use alternative weighting schemes to integrate risk calculations across HVRAs. A further strength is the scalability of the framework, which can be applied from project-level planning to strategic, nation-wide

Despite the strengths of this approach there remain limitations and challenges to address. Understanding current risk is not the same as projecting future risk, which requires prediction of changes in vegetation from natural growth and from other disturbances, changes in demographics and development patterns that could expose more human communities to wildfire risk, the dynamic feedbacks of wildfires changing landscape conditions, and the influences on fire regimes of a changing climate. Characterizing risk is a necessary but not sufficient component to developing, selecting, and implementing mitigation strategies. Information about management opportunities, treatment costs, and their relation to risk factors needs to be considered, as does uncertainty related to science

A number of promising extensions to the work presented in this chapter exist. Embedding geospatial wildfire risk analysis within optimization algorithms could inform multiple applications, for instance pre-positioning aerial firefighting resources, initial attack home base locations and dispatch strategies, fuels and vegetation management, and incident management. Fuel management in particular is a promising avenue for spatially explicit optimization approaches. Increasing use of expert systems plus appropriate fire effects models will enable improved estimates of the consequences of wildfire. Increasing use of multi-criteria decision analysis techniques will enable integrated assessments of risk across social and ecological values, and will facilitate prioritization efforts. Non-market valuation studies could further assist prioritization efforts and articulation of management tradeoffs. One very important, and highly uncertain, topic is the consideration of future wildfire risk

methods to articulate relative importance across HVRAs.

**6. Conclusion** 

analysis.

delivery and policy direction.


The Science and Opportunity of Wildfire Risk Assessment 119

Kaloudis, S., Tocatlidou, A., Lorentzos, N.A., Sideridis, A.B., & Karteris, M. (2005). Assessing

Uncertainty. *Ecological Modelling,* Vol. 181, No. 1, pp. 25-38, ISSN 0304-3800 Keane, R.E., Drury, S.A., Karau, E.C., Hessburg, P.F., & Reynolds, K.M. (2010). A method for

management. *Ecological Modelling*, Vol. 221, No. 1, pp. 2-18, ISSN 0304-3800 Keane, R.E., & Karau, E. (2010). Evaluating the ecological benefits of wildfire by integrating

Kim, Y-H., Bettinger, P., & Finney, M. (2009). Spatial optimization of the pattern of fuel

*Journal of Operational Research*, Vol. 197, No. 1, pp. 253-265, ISSN 0377-2217 Knol, A.B., Slottje, P., van der Sluijs, J.P., & Lebret, E. (2010). The use of expert elicitation in

Konoshima, M., Montgomery, C.A., Albers, H.J., & Arthur, J.L. (2008). Spatial-Endogenous

Kuhnert, P.M., Martin, T.G., & Griffiths, S.P. (2010). A guide to eliciting and using expert

Littell, J.S., McKenzie, D., Peterson, D.L., & Westerling, A.L. (2009). Climate and wildfire

Martin, J., Runge, M.C., Nichols, J.D., Lubow, B.C., & Kendall, W.L. (2009). Structured

Noonan-Wright, E., Opperman, T.S., Finney, M.A., Zimmerman, T., Seli, R.C., Elenz, L.M.,

Prestemon, J.P., D.T. Butry, K.L. Abt, & Sutphen, R. (2010). Net benefits of wildfire

*Management*, Vol. 86, No. 1, pp. 1-13, ISSN 0301-4797

Forest Service, Rocky Mountain Research Station. 60 p..

*Health,* Vol. 9, No. 19, pp. 1-16, ISSN 1476-069X

84, No. 3, pp. 449-468, ISSN 0023-7639

No. 4, pp. 1003-1021, ISSN 1051-0761

pp. 1241-1252, ISSN 0301-4797

749X

1162-1172, ISSN 0304-3800

914, ISSN 1461-023X

Tech. Rep. RMRS-GTR-252. Fort Collins, CO: U.S. Department of Agriculture,

Wildfire Destruction Danger: a Decision Support System Incorporating

mapping fire hazard and risk across multiple scales and its application in fire

fire and ecosystem simulation models. *Ecological Modelling,* Vol. 221, No. 8, pp.

management activities and subsequent effects on simulated wildfires. *European* 

environmental health impact assessment: a seven step procedure. *Environmental* 

Fire Risk and Efficient Fuel Management and Timber Harvest. *Land Economics,* Vol.

knowledge in Bayesian ecological models. *Ecology Letters,* Vol. 13, No. 7, pp. 900-

area burned in western U.S. ecoprovinces, 1916-2003. *Ecological Applications,* Vol. 19,

decision making as a conceptual framework to identify thresholds for conservation management. *Ecological Applications,* Vol. 19, No. 5, pp. 1079-1090, ISSN 1051-0761 Martínez, J., Vega-Garcia, C., & Chuvieco, E. (2009). Human-caused wildfire risk rating for

prevention planning in Spain. *Journal of Environmental Management*, Vol. 90, No. 2,

Calkin, D.E., & Fiedler, J.R. (2011). Developing the U.S. Wildland Fire Decision Support System. *Journal of Combustion*. Doi: 10.1155/2011/168473, ISSN 2090-1976 Parisien, M.A., Junor, D.A., &Kafka, V.G. (2007). Comparing landscape-based decision rules

for placement of fuel treatments in the boreal mixed wood of western Canada. *International Journal of Wildland Fire,* Vol. 16, No. 6, pp. 664-672, ISSN 1049-8001 Prasad, V.K., Badarinath, K.V.S., & Eaturu, A. (2007). Biophysical and anthropogenic

controls of forest fires in the Deccan Plateau, India. *Journal of Environmental* 

prevention education efforts. *Forest Science*, Vol. 56, No. 2, pp. 181-192, ISSN 0015-


Chuvieco, E., Aguado, I., Yebra, M., Nieto, H., Salas, J., Martín, M.P., Vilar, L., Martínez, J.,

Cochrane, M.A., C.J. Moran, M.C. Wimberley, A.D. Baer, M.A. Finney, K.L. Beckendorf, J.

fuel treatments. *International Journal of Wildland Fire*, ISSN 1049-8001 Collins, B.M., Stephens, S.L., Moghaddas, J.J., & Battles, J. (2010). Challenges and

Landscapes. *Journal of Forestry* Vol. 108, No. 1, pp. 24-31, ISSN 0022-1201 Cruz, M.G., & Alexander, M.E. (2010). Assessing crown fire potential in coniferous forests of

Fairbrother, A., & Turnley, J.G. (2005). Predicting risks of uncharacteristic wildfires:

Finney, M.A. (2005). The challenge of quantitative risk analysis for wildland fire. *Forest Ecology and Management,* Vol. 211, No. 1-2, pp. 97-108, ISSN 0378-1127 Finney, M.A., Seli, R.C., McHugh, C.W., Ager, A.A.; Bahro, B., & Agee, J.K. 2007. Simulation

Finney, M.A., McHugh, C.W., Grenfell, I.C., Riley, K.L., & Short, K.C. (2011a). A Simulation

Finney, M.A., Grenfell, I.C., McHugh, C.W., Seli, R.C., Tretheway, D., Stratton, R.D., &

González, J.R., Kolehmainen, O., & Pukkala, T. (2007). Using expert knowledge to model

Gude, P., Rasker, R., & Van den Noort, J. (2008) Potential for Future Development on Fire-Prone Lands. *Journal of Forestry*, Vol. 106, No. 4, pp. 198-205, ISSN 0022-1201 Hessburg, P.F., Reynolds, K.M., Keane, R.E., James, K.M., & Salter, R.B. (2007). Evaluating

Hirsch, K.G., J.A. Podur, R.D. Jansen, R.D. McAlpine & Martell, D.L.(2004). Productivity

*Journal of Wildland Fire,* Vol. 16, No. 6, pp. 712-727, ISSN 1049-8001

*Modeling and Assessment* Vol. 16, No. 2, pp. 153-167, ISSN 1420-2026

*and Management,* Vol. 247, No. 1-3, pp. 1-17, ISSN 0378-1127

*Modelling* Vol 221, No 1, pp. 46-58, ISSN 0304-3800

No. 1-2, pp. 28-35, ISSN 0378-1127

No. 2, pp. 107-114, ISSN 0168-1699

8001

1436-3240

Martín, S., Ibarra, P., de la Riva, J., Baeza, J., Rodríguez, F., Molina, J.R., Herrera, M.A., & Zamora, R. (2010). Development of a framework for fire risk assessment using remote sensing and geographic information system technologies. *Ecological* 

Eidenshink, & Z. Zhu. (In Press) Estimation of wildfire size and risk changes due to

Approaches in Planning Fuel Treatments across Fire-Excluded Forested

western North America: a critique of current approaches and recent simulation studies. *International Journal of Wildland Fire*, Vol. 19, No. 4, pp. 377-398, ISSN 1049-

Application of the risk assessment process. *Forest Ecology and Management*, Vol. 211,

of long-term landscape-level fuel treatment effects on large wildfires. *International* 

of Probabilistic Wildfire Risk Components for the Continental United States. *Stochastic Environmental Research and Assessment*, Vol. 25, No. 7, pp. 973-1000, ISSN

Brittain, S. (2011b) A Method for Ensemble Wildland Fire Simulation. *Environmental* 

forest stand vulnerability to fire. *Computers and Electronics in Agriculture,* Vol. 55,

wildland fire danger and prioritizing vegetation and fuel treatments. *Forest Ecology* 

ofOntario initial attack fire crews: results of an expert-judgment elicitation study. *Canadian Journal of Forest Research,* Vol. 34, No. 3, pp. 705-715, ISSN 0045-5067 Hudak, A.T., Rickert, I., Morgan, P., Strand, E., Lewis, S.A., Robichaud, P.R., Hoffman, C., &

Holden, Z.A. (2011). Review of fuel treatment effectiveness in forests and rangelands and a case study from the 2007 megafires in central, Idaho, USA. Gen. Tech. Rep. RMRS-GTR-252. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 60 p..


**7** 

*P.R. China* 

**Theories and Methods for** 

**the Emergency Rescue System** 

According to the "China State Plan for Rapid Response to Public Emergencies" (hereinafter referred to as "Plan"), which was published by the Central Government of the People's Republic of China, "public emergencies" refer to those emergencies that happened suddenly, and would (or might) cause heavy casualties and property loss, damage ecological environment, bring severe harms to our society and threat public safety. In the "Plan", public emergencies were divided into four categories: natural disasters, accidental

Since long time ago, the progress of human society has been achieved at the cost of deteriorating our living environment. Consequently, the number of natural or manmade disasters has been increasing. Earthquakes, floods, hurricanes, nuclear leakages, sudden outbreak of infectious diseases, fires and explosions attacked the human-beings one after another. For example, the Great Hanshin Earthquake in Japan in 1995, the "September 21" Earthquake in Taiwan in 1998, the "September 11" Terrorist Attack in US in 2001, the "August 14" Power Failure in US and Canada in 2003, and the disastrous Indian Ocean Tsunami in 2005, have brought severe losses to local economy, peoples' life and property. As we all know, public emergencies, particularly natural disasters, are unavoidable. But we could reduce the loss of disasters to a minimum, or even eliminate the negative impact of disasters, by designing an appropriate emergency rescue system. For example, in 2005, the southern United States was attacked by Hurricane Katrina. The local government failed to allocate emergency resources in a timely manner. Consequently, the local people didn't have enough emergency supplies, such as food, drinking water, the necessities of life and medicine. Due to the severe shortage of emergency supplies, many disaster-stricken people resorted to violence. Riots occurred in many places, making the situation even worse.

Another example is the 7.6-magnitude earthquake happened on South Asian Subcontinent in October 2005. The disaster-stricken areas were faced with several problems: 1) Water supply was interrupted. The local residents didn't have food to eat. 2) Hospitals were shut down. The residents were in urgent need of medical care. 3) The traffic conditions were poor

disasters, public emergencies and social security events.

**1. Introduction** 

Jianfeng Li1,2, Wenmao Liu2 and Bin Zhang1 *1School of Environment, Tsinghua University, Beijing, 2Institutes of Education, Tsinghua University, Beijing, 3Beijing Municipal Institute of Labor Protections, Beijing Academy of Science and Technology, Beijing,* 

