Tradeoff between Investments in Infrastructure and Forecasting when Facing Natural Disaster Risk
Hurricane Katrina of 2005 was responsible for at least 81 billion dollars of property damage. In planning for such emergencies, society must decide whether to invest in the ability to evacuate more speedily or in improved forecasting technology to better predict the timing and intensity of the criti...
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ndltd-tamu.edu-oai-repository.tamu.edu-1969.1-ETD-TAMU-2009-05-7492013-01-08T10:41:12ZTradeoff between Investments in Infrastructure and Forecasting when Facing Natural Disaster RiskKim, Seong D.infrastructureforecast qualitynatural disasterhurricaneevacuation speedforecast accuracyhazard riskemergencyHurricane Katrina of 2005 was responsible for at least 81 billion dollars of property damage. In planning for such emergencies, society must decide whether to invest in the ability to evacuate more speedily or in improved forecasting technology to better predict the timing and intensity of the critical event. To address this need, we use dynamic programming and Markov processes to model the interaction between the emergency response system and the emergency forecasting system. Simulating changes in the speed of evacuation and in the accuracy of forecasting allows the determination of an optimal mix of these two investments. The model shows that the evacuation improvement and the forecast improvement give different patterns of impact to their benefit. In addition, it shows that the optimal investment decision changes by the budget and the feasible range of improvement.Bickel, J. Eric2010-07-15T00:13:53Z2010-07-23T21:45:15Z2010-07-15T00:13:53Z2010-07-23T21:45:15Z2009-052010-07-14May 2009BookThesisElectronic Dissertationtextapplication/pdfhttp://hdl.handle.net/1969.1/ETD-TAMU-2009-05-749eng |
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language |
English |
format |
Others
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infrastructure forecast quality natural disaster hurricane evacuation speed forecast accuracy hazard risk emergency |
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infrastructure forecast quality natural disaster hurricane evacuation speed forecast accuracy hazard risk emergency Kim, Seong D. Tradeoff between Investments in Infrastructure and Forecasting when Facing Natural Disaster Risk |
description |
Hurricane Katrina of 2005 was responsible for at least 81 billion dollars of property damage. In planning for such emergencies, society must decide whether to invest in the ability to evacuate more speedily or in improved forecasting technology to better predict the timing and intensity of the critical event. To address this need, we use dynamic programming and Markov processes to model the interaction between the emergency response system and the emergency forecasting system. Simulating changes in the speed of evacuation and in the accuracy of forecasting allows the determination of an optimal mix of these two investments. The model shows that the evacuation improvement and the forecast improvement give different patterns of impact to their benefit. In addition, it shows that the optimal investment decision changes by the budget and the feasible range of improvement. |
author2 |
Bickel, J. Eric |
author_facet |
Bickel, J. Eric Kim, Seong D. |
author |
Kim, Seong D. |
author_sort |
Kim, Seong D. |
title |
Tradeoff between Investments in Infrastructure and Forecasting when Facing Natural Disaster Risk |
title_short |
Tradeoff between Investments in Infrastructure and Forecasting when Facing Natural Disaster Risk |
title_full |
Tradeoff between Investments in Infrastructure and Forecasting when Facing Natural Disaster Risk |
title_fullStr |
Tradeoff between Investments in Infrastructure and Forecasting when Facing Natural Disaster Risk |
title_full_unstemmed |
Tradeoff between Investments in Infrastructure and Forecasting when Facing Natural Disaster Risk |
title_sort |
tradeoff between investments in infrastructure and forecasting when facing natural disaster risk |
publishDate |
2010 |
url |
http://hdl.handle.net/1969.1/ETD-TAMU-2009-05-749 |
work_keys_str_mv |
AT kimseongd tradeoffbetweeninvestmentsininfrastructureandforecastingwhenfacingnaturaldisasterrisk |
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1716504601767706624 |