Prepositioning for flooding in the Sacramento region
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Authors
Farlow, Charles R.
Subjects
Advisors
Date of Issue
2011-03
Date
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
Type
Executive Summary
Description
Executive summary for an NPS thesis: see https//Calhoun.nps.edu/handle/10945/5721
Executive Summary: The Sacramento region is prone to flooding disasters. Although the Sacramento regional authorities and emergency management agencies have been planning in order to control and divert the water flow as much as possible, they also need to prepare emergency assets and personnel for cases where flooding is inevitable. A detailed analysis of the prepositioning of strategic resources before the disaster and its effect on the disaster's aftermath has not been performed. This prepositioning must occur well-in-advance of a disaster. That phase of the plan is important because the efficiency of subsequent logistics (such as the distribution of supplies to affected areas during the disaster) is conditioned by those strategic decisions. This thesis uses a prepositioning model (POM) to represent and analyze the above problem in the Sacramento region. We model a network of eight affected areas (AAs) and ten relief locations (RLs). the RLs have prepositioned resources and shelter. Some RLs have airstrips for air transportation, and medical facilities. The AAs are locations that could be affected by a disaster. The population in these AAs are people who do not successfully evacuate prior to the disaster, and we separate them into three categories dependent on their need. The first category is the emergency population (EP), who are injured and/or in need of emergency evacuation to a facility that can administer medical assistance. The second category of populations is the affected population (AP), who can stay in the AA, but need resources to be delivered in order to survive. The last population is the displaced population (DP), who will need to be transported to a RL for emergency shelter. Each AA has a certain number of each of these three populations in any given scenario. AAs can receive supplies via land or air, depending on their characteristics. The POM recommends where to preposition and/or expand warehouses, health-care personnel, ramp space and transportation vehicle capacity in order to help evacuate the EP, supply resource to the AP, and transport the DP during the first 72 hours after a flood disaster. The POM's main objective is to minimize the expected number of EP and AP casualties. As a secondary objective, the POM maximizes the DP transported to RL shelters. Flooding disasters can cause different damage depending on their location and severity. In this thesis we evaluate four possible scenarios, from a mild flooding to more severe ones where air strips and roads may be impeded or even unavailable. Each scenario has different numbers of EP, AP and DP, calculated as different percentages of the population of the AA, depending on the scenario. We also analyze several budget levels for expansion of the initially prepositioned resources. With the data and assumptions in this thesis, the POM finds that the RLs the Federal Emergency Relief Agency has already selected have enough warehouse space to support the AP in the flooding scenarios assumed in this thesis. Only when the existing warehouse capacity is hypothesized much lower than in our baseline assumption, expansion is recommended. Also, with a minor investment in additional health-care providers and emergency rescue vehicles, all the EP can be rescued and transported to medical facilities for treatment. Additional insights gained from our analysis including the lack of mass housing for the DP. Even if the budget permits the maximum expansions of existing facilities, some DP would still not have shelter. This suggests that other space at hotels or additional RLs must be designated and included at the planning level. According to the data gathered for this thesis, existing ramp space at the AAs is sufficient to offload the commodities delivered by aircraft, and does not need to be expanded. Depending on the scenario, a modest number of additional transportation vehicles are also recommended,
Executive Summary: The Sacramento region is prone to flooding disasters. Although the Sacramento regional authorities and emergency management agencies have been planning in order to control and divert the water flow as much as possible, they also need to prepare emergency assets and personnel for cases where flooding is inevitable. A detailed analysis of the prepositioning of strategic resources before the disaster and its effect on the disaster's aftermath has not been performed. This prepositioning must occur well-in-advance of a disaster. That phase of the plan is important because the efficiency of subsequent logistics (such as the distribution of supplies to affected areas during the disaster) is conditioned by those strategic decisions. This thesis uses a prepositioning model (POM) to represent and analyze the above problem in the Sacramento region. We model a network of eight affected areas (AAs) and ten relief locations (RLs). the RLs have prepositioned resources and shelter. Some RLs have airstrips for air transportation, and medical facilities. The AAs are locations that could be affected by a disaster. The population in these AAs are people who do not successfully evacuate prior to the disaster, and we separate them into three categories dependent on their need. The first category is the emergency population (EP), who are injured and/or in need of emergency evacuation to a facility that can administer medical assistance. The second category of populations is the affected population (AP), who can stay in the AA, but need resources to be delivered in order to survive. The last population is the displaced population (DP), who will need to be transported to a RL for emergency shelter. Each AA has a certain number of each of these three populations in any given scenario. AAs can receive supplies via land or air, depending on their characteristics. The POM recommends where to preposition and/or expand warehouses, health-care personnel, ramp space and transportation vehicle capacity in order to help evacuate the EP, supply resource to the AP, and transport the DP during the first 72 hours after a flood disaster. The POM's main objective is to minimize the expected number of EP and AP casualties. As a secondary objective, the POM maximizes the DP transported to RL shelters. Flooding disasters can cause different damage depending on their location and severity. In this thesis we evaluate four possible scenarios, from a mild flooding to more severe ones where air strips and roads may be impeded or even unavailable. Each scenario has different numbers of EP, AP and DP, calculated as different percentages of the population of the AA, depending on the scenario. We also analyze several budget levels for expansion of the initially prepositioned resources. With the data and assumptions in this thesis, the POM finds that the RLs the Federal Emergency Relief Agency has already selected have enough warehouse space to support the AP in the flooding scenarios assumed in this thesis. Only when the existing warehouse capacity is hypothesized much lower than in our baseline assumption, expansion is recommended. Also, with a minor investment in additional health-care providers and emergency rescue vehicles, all the EP can be rescued and transported to medical facilities for treatment. Additional insights gained from our analysis including the lack of mass housing for the DP. Even if the budget permits the maximum expansions of existing facilities, some DP would still not have shelter. This suggests that other space at hotels or additional RLs must be designated and included at the planning level. According to the data gathered for this thesis, existing ramp space at the AAs is sufficient to offload the commodities delivered by aircraft, and does not need to be expanded. Depending on the scenario, a modest number of additional transportation vehicles are also recommended,
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Operations Research (OR)
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2 p.