A Framework for Enhancing Resilience of Community by Expediting ...
A Framework for Enhancing Resilience of Community by Expediting ...
A Framework for Enhancing Resilience of Community by Expediting ...
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A <strong>Framework</strong> <strong>for</strong> <strong>Enhancing</strong> <strong>Resilience</strong> <strong>of</strong> <strong>Community</strong><br />
<strong>by</strong> <strong>Expediting</strong> Post Disaster Recovery<br />
Abhijeet DESHMUKH 1 and Makarand HASTAK 2<br />
1 PhD student, school <strong>of</strong> civil engineering, Purdue University<br />
(550 Stadium Mall Drive, School <strong>of</strong> Civil Engineering, West Lafayette, IN 47906-2051, United States<br />
E-mail:deshmukh@purdue.edu<br />
2 Pr<strong>of</strong>essor and Head, Construction Engineering & Management, Purdue University,<br />
550 Stadium Mall Dr., West Lafayette, IN, 47906-2051,<br />
E-mail: hastak@purdue.edu<br />
This paper presents a framework <strong>for</strong> increasing resilience <strong>of</strong> a community <strong>by</strong> expediting disaster recovery<br />
through capacity building and enhancing infrastructure per<strong>for</strong>mance. The framework provides a unique<br />
approach to integrate the results available from loss assessment tools and locally available data such as<br />
existing capacities, capacities required and important social and economic activities.<br />
The research is based on the interrelationship between communities, industries and related critical<br />
infrastructure. Provision <strong>of</strong> necessary serviceability level <strong>of</strong> related critical infrastructure to sustain important<br />
social and economic activities and mitigating losses through capacity building will help in recovering within a<br />
desired time frame.<br />
The proposed framework will enable the development <strong>of</strong> a decision making model that will allow city<br />
managers, emergency planners and industry people to recognize the important critical infrastructure, their role<br />
in disaster preparedness and capacities required <strong>for</strong> minimizing social and economic impact which will further<br />
help in developing mitigation strategies.<br />
The decision making model will utilize relevant in<strong>for</strong>mation related to infrastructure and community<br />
attributes available from loss assessment tools such as HAZUS-MH and local data <strong>for</strong> develop effective<br />
mitigation strategies to recover within the required time frame.<br />
Key Words: resilience, recovery phases, social and economic impact, infrastructure, disasters.<br />
1. INTRODUCTION<br />
Recent studies have shown that the world is becoming vulnerable to numerous natural disasters such as<br />
hurricanes, floods, droughts, etc. It is also predicted that the frequency <strong>of</strong> such events will increase in the coming<br />
years making the communities across the world highly vulnerable to disasters.<br />
The impact <strong>of</strong> natural disasters is further escalated <strong>by</strong> failures <strong>of</strong> critical infrastructure in the region. Such<br />
failures are closely related to the conditions <strong>of</strong> critical infrastructure. The majority <strong>of</strong> infrastructure throughout<br />
the U.S. has been weakened due to age and deteriorated conditions, making them vulnerable to natural disasters.<br />
The 2009 ASCE Report Card <strong>for</strong> infrastructure gives an average grade <strong>of</strong> D to U.S. infrastructure signifying a<br />
need <strong>for</strong> urgent rehabilitation ASCE 1) . Leavitt et al. 2) have argued that the failure <strong>of</strong> multiple infrastructure<br />
systems escalated the impact <strong>of</strong> Hurricane Katrina in New Orleans. Flood protection systems such as levee, canal<br />
systems, etc., were constructed to safeguard New Orleans. However, these systems were poorly maintained and<br />
did not withstand the impact <strong>of</strong> the hurricane resulting in widespread damage to New Orleans. Disasters and<br />
aging interdependent infrastructure will increase impact making communities less resilient to disasters Leavitt et<br />
al. 2) .<br />
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This observation was apparent during the 2010 Haiti earthquake which had a catastrophic magnitude <strong>of</strong> 7.0<br />
Mw. Its epicenter was near the town <strong>of</strong> Leogane, approximately 16 miles west <strong>of</strong> Port-au-Prince, Haiti's capital<br />
(Fig.1). The earthquake occurred at 4:53 PM local time on January 12; and, <strong>by</strong> January 24, at least 52<br />
aftershocks, including one measuring 5.9 Mw, were recorded USGS 3) . The earthquake caused major damage to<br />
Port-au-Prince, Jacmel, and other settlements in the region. Amongst the widespread devastation and damage<br />
throughout Port-au-Prince, vital infrastructure, i.e., civil, civic and social infrastructure necessary to respond to<br />
the disaster was severely damaged or destroyed including all hospitals in the capital, the international airport,<br />
and the Port-au-Prince seaport. The main highway linking Port-au-Prince with Jacmel remained blocked <strong>for</strong> ten<br />
days after the earthquake, hampering delivery <strong>of</strong> aid to Jacmel NY<br />
Times 4) . In this research, infrastructure will be classified into three<br />
different types, i.e., civil infrastructure such as utility systems,<br />
transportation systems, etc., civic infrastructure such as hospitals,<br />
emergency centers, etc. and social infrastructure such as religious<br />
centers, homes, etc.<br />
<br />
<br />
the earthquake including healthcare, transportation,<br />
telecommunications, water supply, utilities, and waste disposal. It<br />
took nearly two weeks <strong>for</strong> the medical relief and supplies to reach<br />
the disaster affected areas in Haiti Des Roches et al. 5) . Haiti was not<br />
resilient enough to restore livelihood and recover as desired, from<br />
the aftermath <strong>of</strong> the earthquake.<br />
Fig.1 Map <strong>of</strong> Haiti<br />
Soon after the earthquake, many countries and international donor organizations pledged to provide monetary<br />
aid to Haiti as debt relief and it was expected that with the inflow <strong>of</strong> abundant resources, Haiti would undergo an<br />
expedited recovery smoothly transitioning between recovery phases, i.e., from emergency phase to short term<br />
recovery and from short term recovery to long term recovery.<br />
Due to inefficient provision <strong>of</strong> infrastructure services, even today there are more than 500,000 people living in<br />
temporary shelter and are victims <strong>of</strong> food security TIME 6) . Additionally, Haiti did not have enough resources,<br />
i.e., machines and equipment, skilled manpower, security personnel, medical relief and supplies, etc. to support<br />
not only the recovery and restore the necessary infrastructure required but also to sustain the important activities<br />
required to restore the livelihoods <strong>of</strong> the people.<br />
In this research, the resources available in post disaster situation are identified as the capacity <strong>of</strong> the<br />
community. Ability <strong>of</strong> the community to acquire and utilize additional capacity <strong>for</strong> mitigating impacts in post<br />
disaster situation is defined as capacity building.<br />
The United Nations damage assessment and loss assessment (DALA) methodology and the Federal<br />
Emergency Management Agency (FEMA)-MH are some <strong>of</strong> the loss damage and loss assessment tools<br />
used to assess the damage in terms <strong>of</strong> physical, social and economic aspects. The in<strong>for</strong>mation provided is helpful<br />
in seeking external funds from donor organizations but does not provide an approach on how the damages can be<br />
minimized <strong>by</strong> using the existing capacities <strong>of</strong> the community.<br />
This paper proposes a research framework <strong>for</strong> enhancing resilience <strong>of</strong> community through enhancement <strong>of</strong><br />
infrastructure services and necessary capacity building. The research framework provides an approach to<br />
integrate the in<strong>for</strong>m <br />
HAZUS-MH and locally available data in terms <strong>of</strong> technical, social and economic aspects <strong>for</strong> expediting<br />
community recovery.<br />
This research is based on the thesis that the resilience <strong>of</strong> a community can be enhanced <strong>by</strong> (i) improving the<br />
serviceability <strong>of</strong> infrastructure necessary and (ii) building required capacity to sustain (i) activities specific to<br />
recovery phase (i.e., emergency response, short term recovery or long term recovery) and (ii) activities critical<br />
<strong>for</strong> community livelihood that make social and economic contribution that will minimize the duration <strong>of</strong> overall<br />
recovery.<br />
The activities specific to recovery phases such as debris removal, sheltering <strong>of</strong> survivors, etc. are crucial <strong>for</strong><br />
minimizing the direct impact <strong>of</strong> a natural disasters. In this research, these activities are defined as recovery<br />
activities. Similarly, activities such as commuting, shopping, businesses when per<strong>for</strong>med make social and<br />
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economic contribution. These activities are defined as sustaining activities.<br />
In this research, resilience <strong>of</strong> a community to natural disasters is defined as the ability <strong>of</strong> a community to<br />
expedite community recovery <strong>by</strong> improving the serviceability <strong>of</strong> related infrastructure and effective capacity<br />
building to mitigate phase specific social and economic impacts.<br />
2. PRIOR RESEARCH WORK<br />
(1)Emergence <strong>of</strong> Resilient Communities<br />
Recently, post disaster management agencies have been researching ways that would enable communities to<br />
recover with little or no external assistance Manyena 7) . This was one <strong>of</strong> the several reasons <strong>for</strong> United Nations to<br />
adopt the concept <strong>of</strong> resilience in the Hyogo <strong>Framework</strong> <strong>for</strong> Action 2005-2015: Building the resilience <strong>of</strong> nations<br />
and communities to disasters. Adapting and recovering from the impacts <strong>of</strong> the disaster is a core essence <strong>of</strong><br />
resilience.<br />
(2)Defining and Quantifying <strong>Resilience</strong><br />
UNISDR 8) has <br />
resist, absorb, accommodate to and recover from the effects <strong>of</strong> a hazard in a timely and efficient manner,<br />
including through the preservation and restoration <strong>of</strong> its essential basic structures and functions. They have<br />
provided a 10 point checklist that will help communities prepare, plan and adapt better to disasters. Communities<br />
especially in the developing countries will be greatly benefitted and better prepared to minimize disaster related<br />
social and economic impacts.<br />
In United States, the September 2001 attacks led to focus the ef<strong>for</strong>ts on ensuring the optimal delivery <strong>of</strong><br />
infrastructure services following a disruptive event. The Critical Infrastructure Task <strong>for</strong>ce (CITF) recommended<br />
the Department <strong>of</strong> Homeland Security (DHS) to focus on Critical Infrastructure <strong>Resilience</strong> (CIR) as their<br />
primary objective.<br />
The concept <strong>of</strong> resilience is not new in the field <strong>of</strong> research and because the concept <strong>of</strong> resilience has been<br />
used in many fields, it has made it difficult to have a common definition Mayunga 9), Cutter et al. 10) . <strong>Resilience</strong><br />
has some attributes such as capacity, capability or ability <strong>of</strong> the system to cope with a disruptive event<br />
Mayunga 9) , Vugrin 11) , Manyena 7) , Cutter et al. 10) .<br />
(3)Quantifying <strong>Resilience</strong><br />
Several methodologies have been proposed to quantify and measure resilience <strong>of</strong> different systems such as<br />
infrastructure and communities to disasters. Bruneau et al.12) have proposed a conceptual framework to quantify<br />
seismic resilience <strong>of</strong> communities. The framework assesses community resilience <strong>by</strong> measuring degraded quality<br />
<strong>of</strong> infrastructure over time and uses three complementary measures, i.e., reduced failure probabilities, reduced<br />
consequences from failures and reduced time to recovery.<br />
Miles and Chang13) have developed a simulation model based on fragility curves to measure seismic<br />
resilience <strong>of</strong> communities. They have developed a simulation model, ResilUS that uses markov chains to model<br />
recovery with respect to time <strong>for</strong> assessing seismic resilience <strong>of</strong> community. The model is based on the<br />
relationship between the recovery parameters and recovery activities <strong>of</strong> infrastructure and services. This model<br />
evaluates losses at the business level rather using the census data.<br />
<strong>Resilience</strong> can be measured using various indicators <strong>of</strong> a community Cutter et al.10). A unique approach to<br />
measure resilience using existing capacities <strong>of</strong> communities is proposed <strong>by</strong> Cutter et al.10). They have proposed<br />
a methodology to evaluate resilience <strong>of</strong> communities in the present condition based on a set <strong>of</strong> indicators.<br />
However, Cutter et al.10) have pointed out that national data source is <strong>of</strong>ten outdated and unable to gauge the<br />
impacts at local level. Also, if local data is used, it might be difficult to provide comparative results.<br />
<strong>Resilience</strong> can also be quantified using vulnerability <strong>of</strong> an organization Dalziell and McManus14). They<br />
suggest that the systems resilience can be enhanced <strong>by</strong> increasing their adaptive capacity either <strong>by</strong> incorporating<br />
system redundancy in design that will enable the system to sustain the required function or <strong>by</strong> increasing<br />
<br />
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The research mentioned earlier focuses on the attributes <strong>of</strong> a community such as ability and capacity <strong>of</strong> a<br />
community to respond and adapt to the disruptive event. However, the research does not emphasize the role <strong>of</strong><br />
recovery ef<strong>for</strong>t necessary <strong>for</strong> any system to respond and adapt to a disruptive event. Vugrin et al.11) have<br />
proposed a framework to measure resilience. The framework comprises <strong>of</strong> two components, i.e., systemic impact<br />
<br />
ollowing<br />
disruption. The framework proposed <strong>by</strong> the author is unique as it is one <strong>of</strong> its kinds to include recovery ef<strong>for</strong>t in<br />
measuring resilience.<br />
<strong>Community</strong> resilience is a complex process because <strong>of</strong> the dynamic interaction between various entities.<br />
Literature also emphasizes the importance <strong>of</strong> infrastructure systems in post disaster situation and impact <strong>of</strong><br />
infrastructure per<strong>for</strong>mance on community development. There is modest knowledge on categorizing recovery<br />
process based on the impacts arising over time and mitigating them <strong>by</strong> enhancement <strong>of</strong> related infrastructure<br />
services.<br />
As mentioned earlier, a community will have different recovery phases and each phase will have a specific<br />
need. Some activities and indicators are very critical and need to be per<strong>for</strong>med <strong>for</strong> minimizing social and<br />
economic impact at a specific time. The impacts <strong>of</strong> the communities can be minimized if the per<strong>for</strong>mance <strong>of</strong><br />
infrastructure is enhanced up to a certain necessary level that would be sufficient <strong>for</strong> the community to transit<br />
from one recovery phase to other within the desired time. This research will help in identifying the factors<br />
affecting the duration <strong>of</strong> recovery.<br />
AZUS-MH and UN damage and loss assessment<br />
(DALA) methodology provide a damage and loss assessment report. This in<strong>for</strong>mation when complemented <strong>by</strong> a<br />
specific approach on prioritizing losses and restoring related infrastructure services using required capacity will<br />
enable the decision makers to prepare better recovery strategies.<br />
(4)Disaster Impact Mitigation Support System (DIMSuS)<br />
The underpinnings <strong>of</strong> this research are based on the previous research <strong>of</strong> Oh15) and Deshmukh et al.16).<br />
Oh15) has developed a disaster impact mitigation support system (DIMSuS) <strong>for</strong> identifying region specific<br />
disaster mitigation strategies based on the inter-relationships between infrastructure and communities and<br />
associated industries in terms <strong>of</strong> technical, social, and economic dependencies. DIMSuS comprises <strong>of</strong> criticality,<br />
vulnerability, and severity modules which are the key metrics <strong>for</strong> the framework to understand how critical<br />
infrastructure, industries, and communities are inter-related and how impacts due to natural hazards can be<br />
measured.<br />
The in<strong>for</strong>mation obtained from using DIMSuS is useful <strong>for</strong> a specific scenario. However, DIMSuS does not<br />
provide a time based analysis to mitigate the impact on community due to reduced infrastructure services and<br />
capacity building.<br />
3. DIFFERENT PHASES OF RECOVERY<br />
A disaster affected community undergoes different phases <strong>of</strong> recovery. The Federal Emergency Management<br />
Agency (FEMA) in the United States classifies the recovery phase <strong>of</strong> a disaster affected community into three<br />
temporal phases: emergency response phase, relief phase and recovery phase Comerio17).<br />
Mayunga9) has classified the recovery phases into four categories, i.e., pre disaster, disaster, restoration and<br />
long term recovery. Emergency response is focused on addressing the immediate humanitarian needs <strong>of</strong> the<br />
<br />
actions in these phases include evacuation, emergency rescue, provision <strong>of</strong> food, water, shelter, etc. The duration<br />
<strong>of</strong> the phase can last from 24 hours to 1 week Comerio17). The emergency phase is followed <strong>by</strong> the short term<br />
recovery phase that involves rehabilitation and would focus on restoration <strong>of</strong> both critical and civic infrastructure<br />
services to help sustain community livelihood and businesses which typically lasts 1 week to 6 months<br />
Comerio17).<br />
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Post Disaster Recovery Phases<br />
Recovery<br />
Recovery Activities<br />
Debris Removal<br />
Sheltering <strong>of</strong> survivors<br />
Reconstruction<br />
Emergency<br />
Phase<br />
Short Term Recovery<br />
Sustaining Activities<br />
Businesses<br />
Livelihood<br />
Commuting<br />
Access to medical services<br />
Long Term Recovery<br />
Fig.2 Phases in <strong>Community</strong> Recovery<br />
Time<br />
Finally, the community will undergo long term<br />
recovery that involves the construction <strong>of</strong> destroyed<br />
buildings and infrastructure which may last between 6<br />
months to 10 years Comerio17). Additionally, provision <strong>of</strong><br />
proper hygiene, food and water throughout the recovery<br />
and reconstruction phase minimizes the occurrence <strong>of</strong><br />
epidemics and diseases in the disaster affected areas.<br />
(1)Post Disaster Recovery Phases<br />
(a)Attributes <strong>of</strong> <strong>Community</strong> Recovery and Utilization<br />
<strong>of</strong> Capacities<br />
In post disaster recovery, impacts will be<br />
prioritized and mitigated based on their urgency. These<br />
impacts can be categorized under different recovery phases. As discussed earlier, a post disaster recovery<br />
consists <strong>of</strong> three main phases, i.e., emergency phase, short term recovery and long term recovery.<br />
<strong>Community</strong> recovery is favorable when the impacts are mitigated within desired time. This is possible<br />
when:<br />
The community is able to mitigate the impacts arising as primary impacts with proper utilization <strong>of</strong> the<br />
existing capacities and available serviceability level <strong>of</strong> the infrastructure.<br />
The community is able to enhance the serviceability level <strong>of</strong> infrastructure up to the necessary level that<br />
would enable minimizing the secondary impacts within desired time.<br />
(b)Traits <strong>of</strong> Resilient <strong>Community</strong><br />
Timely mitigation <strong>of</strong> impacts in one phase will lead to the transition <strong>of</strong> a community from one phase to the<br />
other. Thus, a community will undergo an effective and within time, post disaster recovery. Such communities<br />
portray the traits <strong>of</strong> a resilient community.<br />
Depending on the intensity and type <strong>of</strong> disaster, Comerio17) have provided a time frame <strong>for</strong> each phase <strong>for</strong><br />
community recovery (Table 1).<br />
In this research, the above mentioned phases are analogous to emergency phase, short term recovery and long<br />
Table 1 Duration <strong>of</strong> recovery phases<br />
Disaster Type and Intensity<br />
Phase Small and concentrated Disaster Large and complex<br />
Emergency 24hrs 1 week<br />
Relief Phase 1 week Up to 6 months Overlap<br />
Recovery Phase Few months to as long as 10 years<br />
term recovery (Fig.2). The ideal recovery period <strong>for</strong> each phase is assumed to be within the observed periods<br />
with respect to small and large disasters. For example, the ideal recovery rate <strong>for</strong> the emergency phase is<br />
considered to be between 24 hrs and 1 week. Additionally, the serviceability level <strong>of</strong> infrastructure system<br />
required at the end <strong>of</strong> each phase will be obtained from the restoration curves developed using ATC18).<br />
Restoration curves are described on the percentage <strong>of</strong> an infrastructure component that is expected to be<br />
operational as a function <strong>of</strong> time after disasters.<br />
However, the community may be unable to recover within the desired time because <strong>of</strong> the following:<br />
The community may not have enough capacities required to mitigate the impacts within time.<br />
The available infrastructure services are insufficient to provide assistance to mitigate the impacts.<br />
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4. RESEARCH METHODOLOGY<br />
(1) Data Types and Modes <strong>of</strong> Data Collection<br />
Relevant data sources, data types and different aspects <strong>of</strong> data would be identified and the relationship<br />
between community and industry sustenance will be established with the attributes <strong>of</strong> the related critical<br />
infrastructure.<br />
Fig.3 Research <strong>Framework</strong><br />
Based on the research needs, data types will be <strong>of</strong> technical, social and economic aspects (Fig.3).<br />
Identification <strong>of</strong> post-disaster circumstances <strong>of</strong> critical infrastructure.<br />
Collection <strong>of</strong> data points affected <strong>by</strong> disasters such as serviceability level <strong>of</strong> basic critical infrastructure,<br />
relationship between social/economic impacts <strong>of</strong> communities and reliance with critical infrastructure.<br />
Arising impacts <strong>of</strong> community in every phase.<br />
o Social/Economic impacts, activities and functions <strong>of</strong> communities.<br />
Emergency Response and required infrastructure <strong>for</strong> recovery and restoration<br />
o Identification <strong>of</strong> infrastructure and its service enhancement <strong>by</strong> emergency agencies,<br />
governments and non-pr<strong>of</strong>it organization.<br />
Data <strong>for</strong> the research will be collected through survey, personal interviews and results generated from<br />
HAZUS-MH <strong>for</strong> a particular disaster. Government <strong>of</strong>ficials responsible <strong>for</strong> emergency preparedness, engineers,<br />
policy makers, nonpr<strong>of</strong>it organization personnel will be interviewed to collect the necessary post disaster<br />
recovery data.<br />
(2) Use <strong>of</strong> HAZUS-MH<br />
This research aims at taking advantage <strong>of</strong> the already existing HAZUS-MH tool. HAZUS-MH uses the<br />
national database <strong>for</strong> transportation, utility systems and census data <strong>for</strong> communities Scawthorn et al.19). The<br />
datasets obtained from HAZUS-MH are obtained <strong>by</strong> conducting analysis <strong>for</strong> a given region affected <strong>by</strong> a<br />
disaster.<br />
A hypothetical situation was created in which Marion County, Indiana is stuck <strong>by</strong> an earthquake <strong>of</strong> intensity<br />
8.5Mw at a depth <strong>of</strong> 5.5km. Based on the data available through HAZUS-MH, a damage assessment report was<br />
generated. Some <strong>of</strong> the results obtained from the analysis are listed below:<br />
Fig.4 Households without service (result obtained from HAZUS-MH using hypothetical situation)<br />
The in<strong>for</strong>mation available from HAZUS-MH, <strong>for</strong> example, as shown in Fig.4 can be used in aiding recovery<br />
process <strong>of</strong> the community. For example, the damage to the buildings and debris generated can be estimated. The<br />
important activity <strong>of</strong> the community such as rebuilding houses may only be executed once the debris from the<br />
site is removed.<br />
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There<strong>for</strong>e, the debris removal may be an important activity <strong>of</strong> the community in the emergency phase and can<br />
be expedited if the roads and bridges are made functional after the disaster to enable the transportation <strong>of</strong> debris<br />
outside the community.<br />
Based on the above relationship, a decision model will be developed that will incorporate the results from<br />
HAZUS-MH and will aid the decision makers at various administration level to prepare better community<br />
recovery strategies <strong>by</strong> allocating resources efficiently <strong>for</strong> enhancing infrastructure per<strong>for</strong>mance. Additionally,<br />
the results generated in HAZUS-MH include infrastructure functional and per<strong>for</strong>mance loss, physical damage<br />
which are obtained as a function <strong>of</strong> time.<br />
5. DEVELOPMENT OF DECISION MAKING MODEL<br />
(1)Assessing the enhancement <strong>of</strong> <strong>Resilience</strong> and Capacity Building<br />
If additional capacities could be provided and the services <strong>of</strong> infrastructure enhanced, the recovery rate in each<br />
phase would be expedited. A hypothetical situation is explained where a community is undergoing through a<br />
post disaster recovery. The above research concept is explained using the emergency phase. The in<strong>for</strong>mation<br />
with respect to infrastructure, community and capacity available in the emergency phase only are illustrated in<br />
Table 2. The assessment <strong>of</strong> enhancement <strong>of</strong> resilience and capacity building is explained via the following steps.<br />
Important<br />
Activities in post<br />
disaster<br />
community<br />
a. Evacuation<br />
and rescue<br />
mission<br />
b. Provision <strong>of</strong><br />
basic<br />
supplies<br />
c. Temporary<br />
shelter,<br />
etc..<br />
Infrastructure<br />
Types<br />
Civil<br />
Table 2 Emergency phase <strong>for</strong> the hypothetical situation<br />
a. Water<br />
b. Electricity<br />
c. Transportation<br />
systems<br />
Civic<br />
a. Hospitals<br />
b. Emergency<br />
centers<br />
Social<br />
a. Homes, etc.<br />
Post Disaster<br />
Serviceability<br />
(Measured in<br />
Terms <strong>of</strong><br />
damage)<br />
(obtained from<br />
HAZUS-MH)<br />
Gap in<br />
required<br />
serviceability<br />
50% 5%<br />
Resources Available<br />
Resour<br />
ces<br />
Capacity<br />
(#)<br />
Resources<br />
Required<br />
(to<br />
mitigated<br />
impacts<br />
within ideal<br />
time)<br />
Trucks 2 4<br />
EMS<br />
vehicles<br />
Hospital<br />
beds<br />
5 20<br />
150 300<br />
Duration <strong>of</strong><br />
the phase<br />
with available<br />
resources<br />
Exceeding<br />
the ideal<br />
recovery<br />
period<br />
(a) Step1: Identification <strong>of</strong> impacts<br />
and important social and economic<br />
activities.<br />
The important activities <strong>of</strong> each phase<br />
will be identified. For example, some <strong>of</strong><br />
the important activities <strong>of</strong> the<br />
emergency phase may include, rescue<br />
missions, provision <strong>of</strong> medical services,<br />
temporary shelter, debris removal, etc.<br />
(b) Step2: Identification <strong>of</strong> related<br />
infrastructure and capacities<br />
required<br />
Once the important activities<br />
have been identified, the related critical<br />
infrastructure and capacities necessary<br />
to sustain the activities. Additionally,<br />
the existing serviceability level <strong>of</strong> infrastructure in post disaster situation and the capacities to enhance the<br />
serviceability will be identified. As shown in Table 2, the activities can be sustained using 50% serviceability<br />
level <strong>of</strong> water system. Also, the resources required to mitigate the impacts are indicated in the resources column.<br />
For example, the community hospital has 150 beds to accommodate the victims. At the same time, the hospital<br />
will be able to function using 50% <strong>of</strong> the water system services.<br />
(c) Step3: Estimation <strong>of</strong> time required to mitigate the impacts and sustain activities<br />
Based on the available capacities and infrastructure serviceability level, time required to sustain activities<br />
completely will be determined. This will also help in determination <strong>of</strong> the duration <strong>of</strong> a given phase. Based on<br />
the capacities available, the emergency phase might complete in 10 days using the serviceability level <strong>of</strong> various<br />
infrastructure systems and the existing capacities which exceeds the desired completion period.<br />
(d) Step4: Estimation <strong>of</strong> additional capacities and infrastructure services enhancement required <strong>for</strong> phase<br />
completion within desired time<br />
The timely execution and completion <strong>of</strong> recovery phases may require the enhancement <strong>of</strong> services <strong>of</strong> critical<br />
infrastructure and acquisition and utilization <strong>of</strong> additional capacities.<br />
The infrastructure services may not be sufficient to enable phase completion within the desired time. For<br />
example, the bridges may be able to provide 30% serviceability that might not be sufficient to sustain the major<br />
activities efficiently. An additional 30% <strong>of</strong> bridge serviceability might be required to complete the emergency<br />
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Infrastructure per<strong>for</strong>mance<br />
Pre disaster situation<br />
t0<br />
Ideal Recovery Period<br />
t1 t4 t2<br />
Enhanced Recovery Rate (Capacity Building)<br />
Post disaster situation<br />
Recovery e Rate<br />
with available<br />
capacities<br />
t0 = time when the recovery starts, t1 = Ideal Recovery time, t2 = Ideal Recovery time, t3 = recovery time based<br />
on available capacities and infrastructure services, t4 = recovery time based on capacity building and enhance <strong>of</strong><br />
infrastructure per<strong>for</strong>mance<br />
Fig.5 Assessing enhancement <strong>of</strong> resilience<br />
t3<br />
Time (t)<br />
phase within the desired time.<br />
Similarly, the community has 2<br />
trucks and 2 cranes to support<br />
<br />
activity <strong>of</strong> the emergency<br />
phase. The available capacities<br />
might be insufficient to<br />
complete the activities within<br />
the required time. In order to do<br />
so, a total <strong>of</strong> 4 trucks and 5<br />
cranes might be required to<br />
mitigate the impacts in required<br />
time. Thus, addition <strong>of</strong> 2 trucks<br />
and 3 cranes is required to build<br />
the necessary capacity <strong>for</strong><br />
sustaining the activities.<br />
(e) Step5: Enhancement <strong>of</strong><br />
resilience and capacity building<br />
Capacity Building during recovery and enhancement <strong>of</strong> infrastructure serviceability will expedite recovery<br />
focusing on the reduction in the recovery period. Based on the proposed thesis, Fig.5 illustrates an approach <strong>for</strong><br />
assessing resilience <strong>by</strong> expediting community recovery. The reduction in time due to capacity building and<br />
enhancement <strong>of</strong> infrastructure serviceability will enhance the resilience <strong>of</strong> the community to disasters.<br />
6. EXPECTED RESULTS AND CONCLUSION<br />
Based on the phase specific impacts, mitigation strategies can be proposed that will enable communities to<br />
better respond to natural disasters.<br />
o Prioritizing rehabilitation <strong>of</strong> damaged infrastructure towards impacts <strong>of</strong> affected communities and<br />
industries with respect to the recovery phase.<br />
o Focused towards provision <strong>of</strong> rapid disaster relief <strong>by</strong> identification <strong>of</strong> most critical infrastructure which<br />
connects areas affected <strong>by</strong> disasters.<br />
o Current situation <strong>of</strong> resource allocation and capacity building (i.e., medical supplies, mobile field<br />
hospitals, food, drinking water, temporary shelters and basic utilities, etc.) based on the affected or<br />
limited infrastructure.<br />
o Provide in<strong>for</strong>mation <strong>for</strong> the long term planning <strong>for</strong> city redevelopment based on prioritized critical<br />
infrastructure and their location.<br />
o Identifying and <strong>for</strong>tifying the existing critical infrastructure to protect communities and industries against<br />
potential disasters in the future.<br />
This paper proposes a research framework <strong>for</strong> developing a decision model that will enable communities to<br />
expedite post disaster recovery <strong>by</strong> capacity building that will facilitate enhancement <strong>of</strong> critical infrastructure<br />
per<strong>for</strong>mance necessary to sustain important activities in the post disaster period. Additionally, this research will<br />
also develop a framework to strategically allocate required resources <strong>for</strong> expediting recovery process.<br />
The research will provide a scientific approach in integrating results from loss assessment methodologies that<br />
exists today in a decision making model that would enable effective allocation <strong>of</strong> available resources <strong>for</strong> not only<br />
addressing the impacts <strong>of</strong> the community <strong>by</strong> enhancing the per<strong>for</strong>mance <strong>of</strong> related critical infrastructure.<br />
Additionally, this research will integrate data available from loss assessment tools such as DALA methodology<br />
and HAZUS-MH developed <strong>by</strong> FEMA with the locally available data such as existing capacities, important<br />
social and economic contributing activities that will enable decision makers to prepare better mitigation<br />
strategies and expedite the recovery process. The foundation <strong>of</strong> this research is based on the previous work done<br />
<strong>by</strong> Oh15) and Deshmukh16) that focuses on identifying the importance <strong>of</strong> restoring critical infrastructure <strong>for</strong><br />
minimizing social and economic impacts.<br />
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