Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 1 Risk-Based Management of Hurricane Preparedness and Recovery for a Highway Agency Presented to the Virginia Department of Transportation Steering Committee by the Center for Risk Management of Engineering Systems March 19, 2000

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 2 VDOT Steering Committee Virginia Department of Transportation Travis Bridewell Mac Clarke Perry Cogburn Jon DuFresne Stephany Hanshaw Steve Mondul Murali Rao Bob Rasmussen J.R. Robinson Gerald Venable Virginia Transportation Research Council Wayne Ferguson

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 3 Stakeholders Newport News Police Virginia Beach Police Norfolk Police Franklin Police Chester Police OBICI Hospital Red Cross Norfolk Emergency Operations Center Virginia Department of Emergency Services Virginia State Police VDOT Traffic Engineering VDOT ITS Sentara Hospitals Virginia Beach Fire Virginia Beach Office of Emergency Management Virginia Port Authority Virginia Department of Rail and Public Transportation

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 4 University of Virginia Graduate Student Richard D. Moutoux Undergraduate Students Ryan M. Finseth Linn H. Koo Clare E. Patterson Timothy J. Zitkevitz Faculty James H. Lambert, Research Assistant Professor of Systems Engineering Yacov Y. Haimes, Quarles Professor of Systems and Civil Engineering Garrick E. Louis, Assistant Professor of Systems Engineering Project website:

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 5 Progress Reviews Stakeholders workshop – February 28, 2000 Hampton Roads Planning District Commission (HRPDC) – April 5, 2000 Virginia Department of Emergency Management (VDEM) – October 6, 2000 Steering committee – December 2, 1999 and December 12, 2000

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 6 Overview of Presentation Introduction Overview of approach Risk-based prioritization of recovery Decision support for resource allocation Agency coordination of recovery schedule Trade-off analysis of recovery and preparedness alternatives Equipment enhancement Use of hurricane forecasts

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 7 Motivation Restore mobility as quickly as possible Currently no formal highway recovery methodology exists Justify aid from FEMA and FHWA Potential for $30-60 billion in losses for a category IV hitting Tidewater, Richmond, or Northern Virginia (Source: Post Hurricane Recovery Workshop, Insurance Institute, 1997)

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 8 Saffir-Simpson Hurricane Categories

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 9 U.S. Mainland Hurricane Strikes (NHC, 1999)

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 10 Hurricane Floyd Hurricane Floyd hit Suffolk District in mid- September, causing significant flood damage 56 deaths made Floyd the deadliest US hurricane since Agnes in 1972 Roads did not receive much wind damage, but flooding closed many roads in Virginia

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 11 Hurricane Floyd (cont.)

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 12 Project Goal The goal of the effort is to improve hurricane preparedness and recovery of the Virginia Department of Transportation through the identification of planning and management options and the assessment and evaluation of the associated costs, benefits, and risks

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 13 Task 1: Review of Literature and Formation of Advisory Committees Review and evaluation of past studies, theory and methodology, other agencies' experience, and databases Two advisory committees: (1) Steering Committee, consisting primarily of VDOT personnel; and (2) a Users' Group, made up of localities and other government agencies, e.g., emergency services.

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 14 Task 2. Extension of Prioritization Tool to GIS Platform Integrate the mapping of critical facilities with VDOT's capabilities for geographic information system (GIS) Work closely with the Transportation Information Management Steering Committee (TIMSC) and current managers of VDOT information systems, including GIS, to ensure compatibility.

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 15 Task 3. Incorporation of Localities and Additional Critical Facilities Local jurisdictions Intermodal connections (ports, airports, rail) Number of people served Logistic points (e.g., food warehouses, power generation facilities, water bottling plants, natural gas pipeline heads, collection and distribution points).

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 16 Task 4. Use of Hurricane Forecasts for VDOT Operations National Hurricane Center and others The effort will demonstrate the efficacy of probabilistic hurricane forecasts in support of various VDOT planning and management functions. Capture the impacts of current decisions to future options

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 17 Task 5. Modeling for Agency-Wide Preparedness and Recovery Hierarchical holographic modeling (HHM) will be used to classify overlapping and connected functions, divisions, and performance metrics Similar studies for the DoD, FBI, and PCCIP Foundation for resource allocation and coordination within and outside agency

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 18 Task 6. Resources, Databases, and Software Task 7. Reports, Presentations, and Workshop

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 19 Overview of Approach

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 20 HHM for Preparedness

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 21 Abbreviated HHM

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 22 Organizational HHM

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 23 Sample Trade-Off Analysis

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 24 Option3 Status Quo Option2 Option1 Trade-Off Analysis (cont.)

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 25 Risk-Based Prioritization of Recovery

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 26 Features of Priority Setting Importance of roads and intersections based on critical facilities and condition of road network Restoring or replacing damaged equipment Critical facilities are those necessary for a community’s well-being

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 27 Classification of Critical Facilities

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 28 Critical Facilities

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 29 Geographic Information Systems Build on an existing GIS database of VDOT roads Network modeling used to create prioritization tool Using Microsoft Excel for optimization and user functionality

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 30 Electronic Road Map Two sources for electronic road maps VDOT’s “Network Level Basemap” –Used to establish road system from which network model will be created Census maps obtained from UVA Library –Used for geocoding addresses

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 31 Example of Arcview Map Suffolk District Hampton Roads Emporia Williamsburg Eastern Shore

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 32 Facility Data Acquisition Worked with the Hampton Roads Planning District Commission to get data on locations of critical facilities Facility data also collected by geocoding addresses in Arcview Critical facilities stored by category and sub-category

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 33 Norfolk Roads and Facilities

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 34 Data Summary Data gathered includes critical facilities, population, highway mileage, and connections Data is imported into Excel using a grid system Data is used to create a prioritization model in Excel

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 35 Excel Grid Method Microsoft Excel is used for the prioritization model A map is in the background of a spreadsheet for spatial reference In addition to being much easier for VDOT to use, the spreadsheet format makes modeling straightforward

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 36 Sample Excel Grid Method

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 37 Arcview Grid

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 38 Prioritization in Excel Spreadsheet layers contain facilities, road mileage, population, etc. Priority metrics are calculated across the grid Priorities are reflected by color-coding grid elements

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 39 Sample Categorical Prioritization

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 40 Decision Criteria The following types of data can be used for spreadsheet prioritization: –Population –Roadway mileage by road type (Interstate, US highway, or primary route) – three different measurements –Critical facilities by category (eight categories) All combinations are possible

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 41 Operating the Prioritization Tool All that is required is an entry of one or zero in each box of this table A one includes that category in the calculation This example does not break down the road types or the many categories of facilities

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 42 Prioritization Tool Example

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 43 Prioritization Example (cont.)

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 44 Calibration of Tool

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 45 Local and Region-wide Models

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 46 Sensitivity Analysis

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 47 Temporal Priorities The model will prioritize recovery differently based on short, medium, and long-term goals Certain facilities are most important immediately after a disaster, and others are needed further down the road Since the Excel model includes data for all categories of facilities, roads, and population, these changes will be simple to implement

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 48 Phases of Preparedness ….

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 49 Decision Support for Resource Allocation

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 50 Motivation Hurricane Floyd struck Virginia in September 1999 and resulted in severe damage from flooding Over 100,000 phone calls to Emergency Operations Center as a result Large scale of disaster makes it difficult to appreciate where the resources are going

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 51 Objective To develop a methodology to support in decision-making for resource allocation and in communicating and substantiating its rationale for its decisions regarding resource allocation for highway recovery from a natural disaster.

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 52 Factors Impacting Resource Allocation Tool tests recovery projects against multiple objectives in order to offer an idea of priority of the projects Effective performance criteria needed –Risk reduction –Performance gain –Resources

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 53 Data Collection Case study performed using data from Hurricane Floyd recovery supplied by VDOT Data includes statistics from 39 counties/cities and 15 types of recovery/preparedness activity Data provided by Perry Cogburn, 2000.

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 54 Data Collection (cont’d)

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 55

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 56

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 57 Data Collection (cont’d) Performance indices must be generated from the data Lack of risk and performance data lead to the development of new indices –Average Daily Traffic(ADT) For each road type(interstate, primary, secondary) –Population Density For all 39 counties/cities

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 58 Hurricane Floyd Projects

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 59

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 60

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 61 AVERAGE DAILY TRAFFIC POPULATION PER SQUARE MILE

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 62 Comparative Analysis of Delays in Hurricane Recovery

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 63 Motivation Individual delays can be modeled in PERT or CPM as in prior UVa/VTRC efforts Need for systematic reporting of delay conditions Need for coordination to reduce the overall time to recovery

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 64 Data Collection Interviews of Virginia agencies involved in the recovery process Specifically the situations in which they are depending or dependent on VDOT Currently conducting interviews of Florida agencies

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 65 Data Collection (cont.) Meeting with Susan Maddox Toth of VDOT’s EOC in Fall 2000 Liaison with VDEM in Fall 2000 who are making similar efforts Past report by UVa/VTRC regarding a specific delay

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 66 Outline of Interviews with DOTs and Agencies 1.What are the cases in which your agency waited on VDOT to be able to start a recovery activity? What are the cases in which VDOT was waiting on your agency? (For example, authorization, materials, personnel, etc.) 2.If not in the past, can you see your agency waiting on VDOT or VDOT waiting on your agency for a recovery activity in the future? Under what circumstances?

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 67 Outline of Interviews with DOTs and Agencies (cont.) 3.Is there anything VDOT could have done to better minimize the delay of recovery? Does your agency have any suggestions for improvement? 4.Is there a particular system or geographic area with which your agency is concerned for the recovery?

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 68 Virginia Agencies Contacted: * Attended Stakeholders Meeting 2/00

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 69 Virginia Agencies Contacted (cont.) * Attended Stakeholders Meeting 2/00

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 70 Virginia Agencies Contacted (cont.) * Attended Stakeholders Meeting 2/00

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 71 Sample of Delay Scenarios

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 72 Sample of Delay Scenarios (cont.)

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 73 Delay Scenarios The following are the delay scenario descriptions that are indicated in the table above: 2A: A potential delay could take place between the time when the Henrico County Division of Fire requests materials over the phone from VDOT such as sand bags and the time when they actually receive it. –(R. C. Dawson, Jr., Deputy Fire Chief, Henrico County Division of Fire, Oct. 9, 2000) 2B: A potential delay could take place between the time when the Henrico County Division of Fire requests equipment over the phone from VDOT such as traffic barricades and the time when they actually receive it. –(R. C. Dawson, Jr., Deputy Fire Chief, Henrico County Division of Fire, Oct. 9, 2000)

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 74 Delay Scenarios (cont.) 2C: A potential delay could take place between Henrico County Division of Fire if there is an inadequate number of on-call personnel at VDOT during emergency response. (R. C. Dawson, Jr., Deputy Fire Chief, Henrico County Division of Fire, Oct. 9, 2000) 11A: Obici Hospital had to wait on VDOT for the availability to current, updated road status and closure information during the recovery of Hurricane Floyd. (Randy Vick, Obici Hospital, Oct. 17, 2000)

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 75 Delay Scenarios (cont.) 11B: Obici Hospital experienced delays during recovery from Hurricane Floyd because the road status information that was provided by VDOT was inaccurate. (Randy Vick, Obici Hospital, Oct. 17, 2000) 12A: The response of the Office of Emergency Medical Services in the future to an isolated area could be delayed if there is a road or bridge failure that is waiting to be repaired by VDOT. (C. Everette Vaughan, Jr., Director of Emergency Operations at the Office of Emergency Medical Services, Oct. 9, 2000)

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 76 Delay Scenarios (cont.) 12B: The Office of Emergency Medical Services had to wait on VDOT for the availability to current, updated road status information during the recovery of Hurricane Floyd. (C. Everette Vaughan, Jr., Director of Emergency Operations at the Office of Emergency Medical Services, Oct. 9, 2000) 12C: The Office of Emergency Medical Services’ response to Franklin, VA during the recovery from Hurricane Floyd was delayed because the road status and closure information provided by VDOT was inaccurate. (C. Everette Vaughan, Jr., Director of Emergency Operations at the Office of Emergency Medical Services, Oct. 9, 2000)

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 77 Delay Scenarios (cont.) 29A: The Department of Conservation and Recreation could potentially be waiting on VDOT in the future to make a bridge or road passable. (Corey Garyotis, Senior Floodplain Engineer, Dept. of Conservation and Recreation, Oct. 10, 2000) 36A: VDOT could potentially be waiting on the Dept. of Mines, Minerals, and Energy in the future to provide geological information or information on where road building materials can be found. (Cheryl Cashman, Dept. of Mines, Minerals, and Energy, Oct. 20, 2000) 36B: see 36A

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 78 Inter-Agency Delays

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 79 Measuring Delays

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 80 Measuring Severity The severity of the length of time of delay is relative to the time horizon: - Short Term (hours, days), - Medium Term (days, weeks) - Long Term (months, years)

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 81 Example Delay Scenario A power line is in a tree blocking a primary road VDOT waits on the electric utility to check status of line before clearing tree from road The road is impassable until the tree is removed

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 82 Example Delay Scenario

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 83 Example Delay Scenario HIGH MODERATE LOW

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 84 Comparing Multiple Delay Scenarios

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 85 Trade-Off Risk-Based Analysis

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 86 Tradeoff Analysis Uncertain Benefits Uncertain Costs

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 87 Examples of Vulnerable Systems Equipment –Signs, signals, and lights Road systems –Roads, bridges, and tunnels Smart highway systems –Motion detectors, cameras, and traffic alert signs

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 88 Types of Preparedness Redundancy: Keeping additional spares on hand or adding extras to the system Resilience: A system that can bounce back after a hurricane. Robustness: The physical strength of a system

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 89 Planning Horizons Pre-event planning horizons –Short term: Preparing the system once a hurricane watch has been announced (hours to days before) –Medium term: Preparing the system at the start of the upcoming hurricane season (weeks to months before) –Long term: Preparing the system for an unknown hurricane in the future (years before)

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 90 Planning Horizons (cont.) Post-event planning horizons –Short term: Repairing the system immediately after or during the hurricane (hours to days after) –Medium term: Repairing the system after all short term problems are fixed (weeks to months after) –Long term: Repairing the system after all other non- long term problems are fixed (months to years after)

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 91 Assessments of Benefits Time savings: How much time VDOT saves in man hours from the alternative Cost savings: How much money is saved from each alternative Lives saved: Number of human lives saved from the alternative Economic impact: Impact on the society and the commerce in the area Environmental impact: Impact on not only the environment but also the animals in the area too Private equipment saved: Amount of personal property saved from the alternative

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 92 Mechanisms of Hurricane Impacts and Preparedness Maximum wind velocity: Top maximum stainable wind that the road system can withstand Storm surge height: Maximum amount of water in flooding and storm surge height that the road system can withstand Sustainable traffic flow: Maximum amount of traffic that the road system can handle without failing

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 93 Saffir-Simpson Hurricane Categories

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 94 Example 1: Smart Highways

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 95 Example 1: Planning Horizons

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 96 Example 1: Assessment of Benefits

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 97 Example 1: Mechanisms of Hurricane Impact and Preparedness

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 98 Equipment Enhancement

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 99 Example of Damage Assessment

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 100 Multiple Enhancement Levels Three enhancement levels for each grade or performance measure are shown in this example

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 101 Mechanism of Hurricane Impact to Road Systems * Assessments of (High, Med, Low) are tentative

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 102 Example of Data Requirements

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 103 Example of an Enhancement Trade-Off Analysis

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 104 Example Trade-Off Analysis

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 105 Sample User Input Worksheet *This is only a screen shot. Values within model are not realistic

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 106 Sample Impact Values *This is only a screen shot. Values within model are not realistic

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 107 Use of Hurricane Forecasts

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 108 Use of Hurricane Forecasts

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 109 Use of Forecasts (cont.)

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 110 Forecasts Policy Options

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 111 Forecasts Tradeoff Analysis

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 112 Forecasts Tradeoff Analysis

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 113 Summary Recommendations

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 114 Priority Setting Consider a systematic approach to priority-setting for recovery Adopt the grids for priority-setting with various grid-size resolutions (District, Residency, smaller) Adopt the demonstrated metrics (populations, mileages,stakeholder facilities, etc.) Consider adding a metric to represent the degree of recovery Use the developed software downloads

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 115 Resource Allocation Consider a systematic approach to resource allocation for recovery Represent the variety of recovery projects across regions Discover the balance among all project impacts and costs Use the approach to improve the allocation of resources to diverse projects Project from past storms to the needs arising from future storms

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 116 Management of Delays Consider a systematic approach to delays in preparedness and recovery Characterize delays in the short, medium, and long terms, pre- and post-event Identify intra- and inter-agency dependencies Use multiple metrics to compare the diverse sources of delay Focus resources on the delays that are most critical to the overall recovery

Center for Risk Management of Engineering Systems University of Virginia, Charlottesville 117 Risk-Cost-Benefit Analysis Consider a systematic approach to cost-benefit analysis of recovery/preparedness Identify the variety of options for redundancy, robustness, and resilience Use the developed software to prepare cost-benefit analyses for diverse systems Consider the use of seasonal and monthly forecasts to aid in preparedness Continue to update the hierarchical holographic model of hurricane preparedness and recovery