Coastal Louisiana Risk Assessment Model

Coastal Louisiana Risk Assessment Model: Technical Description and 2012 Coastal Master Plan Analysis Results

Jordan R. Fischbach
David R. Johnson
David S. Ortiz
Benjamin P. Bryant
Matthew Hoover
Jordan Ostwald
Copyright Date: 2012
Published by: RAND Corporation
Pages: 144
https://www.jstor.org/stable/10.7249/j.ctt3fh0bx
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  • Book Info
    Coastal Louisiana Risk Assessment Model
    Book Description:

    Describes the Coastal Louisiana Risk Assessment (CLARA) model developed by RAND to estimate flood depths and damage that occurs as a result of major storms in Louisiana’s coastal region. CLARA made it possible to evaluate potential projects for inclusion in the Louisiana’s 2012 Coastal Master Plan on the basis of how well they reduce flood damage over the next fifty years. Also describes damage reduction provided by the final Master Plan.

    eISBN: 978-0-8330-7985-5
    Subjects: Political Science, Environmental Science, History

Table of Contents

  1. Front Matter
    (pp. i-ii)
  2. Preface
    (pp. iii-iv)
  3. Table of Contents
    (pp. v-viii)
  4. Figures
    (pp. ix-x)
  5. Tables
    (pp. xi-xii)
  6. Summary
    (pp. xiii-xxii)

    Motivated in part by the devastating effects of Hurricanes Katrina and Rita in 2005 and Gustav and Ike in 2008, planners and policymakers in the State of Louisiana have updated Louisiana’s Comprehensive Master Plan for a Sustainable Coast (the “Master Plan”). The resulting Master Plan proposes a range of structural protection and coastal restoration projects to reduce storm surge flood risks to coastal communities and address other objectives to help create a more sustainable coast over the next 50 years. To support this process, the Coastal Protection and Restoration Authority of Louisiana (CPRA) convened a set of modeling teams to...

  7. Acknowledgments
    (pp. xxiii-xxiv)
  8. Abbreviations
    (pp. xxv-xxvi)
  9. CHAPTER ONE Introduction
    (pp. 1-6)

    Coastal Louisiana’s built and natural environment faces risks from catastrophic tropical storms, of which Katrina and Rita in 2005 and Gustav and Ike in 2008 are among the most recent. Hurricanes flood cities, towns, and farmlands, forcing evacuations, damaging and destroying buildings and infrastructure, eroding wetlands, and threatening the health and safety of residents.

    The State of Louisiana responded to the threat of catastrophic hurricanes by engaging in a new planning process to support the development of Louisiana’s Comprehensive Master Plan for a Sustainable Coast (the “Master Plan”) (Coastal Protection and Restoration Authority of Louisiana [CPRA], 2012a). The Master Plan...

  10. CHAPTER TWO Overview of CLARA
    (pp. 7-22)

    CLARA’s structure is based on well-described principles of quantitative risk analysis. Mathematically, risk is typically described as the product of the probability or likelihood of a given event occurring—in this case, the annual probability of storm surge flooding occurring at different depths—and the consequences of that event. This formulation can be further refined when applied to storm surge flood risk because engineered systems designed to prevent flooding—which do not always function as designed and can themselves fail—introduce a new dimension of uncertainty.

    As a result, the likelihood of flooding can be divided into two components: the...

  11. CHAPTER THREE Measuring Hurricane Hazard and Flood Recurrence
    (pp. 23-28)

    This chapter provides information on how the flood depth module operates to produce estimates of flood exceedances, starting from a limited set of simulated storm inputs. The underlying statistical method for estimating flood exceedances is described, along with details on how the storm inputs were chosen for this application to the Louisiana coast. The basic structure of the flood depth module is also provided, although details of each component module are left for later chapters.

    The statistical methodology that produces estimates of damage at different flood exceedances and EAD calculated by CLARA is derived from the JPM-OS method initially applied...

  12. CHAPTER FOUR Calculating Surge and Wave Overtopping
    (pp. 29-34)

    This chapter describes the calculations performed in the overtopping submodule shown in Figure 2.3. During a storm event, overtopping occurs as a result of water entering the protection system because of waves spilling over a protective structure or storm surge pouring over the crest of the structure. The Storm Surge/Wave Team uses hydrodynamic models to generate the input data for the calculation of wave and surge overtopping.

    We use two-dimensional weir equations from Meer (2002) and Franco and Franco (1999) to calculate overtopping rates (volume per time per linear distance along a protective structure) at each time step of the...

  13. CHAPTER FIVE Estimating Protection System Fragility
    (pp. 35-44)

    This chapter describes the calculation steps in the system fragility module shown in Figure 2.3 in Chapter Two. An important component of flood risk is the reliability of the structures designed for flood defense. These protection systems contain many components, each with several failure modes. Conceptually, it is possible to build a detailed, physics-based model to capture the full range of failure mechanisms for hurricane protection structures. In reality, however, empirical measurement would be difficult, if not impossible, for some parameters. Therefore, most analyses of failures in such systems are probabilistic and based on approximations. A failure is defined as...

  14. CHAPTER SIX Calculating Interior Drainage in Protected Areas
    (pp. 45-54)

    This chapter describes the calculation steps for the interior drainage module shown in Figure 2.3 in Chapter Two. The interior drainage module relates flooding and breaching around the boundaries of protected areas to the final flood elevations in each BHU in the protected area. In other words, it takes outputs from the overtopping and system fragility modules and determines how any resulting floodwaters are distributed through the interior of the protection system. This is a time-stepped equilibrium-based model: It does not dynamically track three-dimensional or even two-dimensional flows but instead distributes volumes at equilibrium among connected basins. This is the...

  15. CHAPTER SEVEN Assessing Economic Value, Growth, and Flood Damage
    (pp. 55-64)

    CLARA estimates the direct economic impacts of flooding by census block at several years between 2011 and 2061. The model employs methods that closely parallel those used by the LACPR (USACE, 2009b) and FEMA Hazus-MH MR4 flood risk models (FEMA, 2009). Damage is estimated for the following categories of assets:

    single-family residences

    manufactured homes

    small multifamily residences (e.g., duplex, triplex)

    large multifamily residences (e.g., apartment building, condominium complex)

    commercial

    industrial

    public facilities

    transport infrastructure (e.g., roads, bridges, rail)

    vehicles

    agriculture structures and properties

    agricultural crops.

    A summary of the economic module calculation steps is shown in Figure 7.1. For these...

  16. CHAPTER EIGHT Uncertainty in CLARA
    (pp. 65-72)

    A key objective of risk analysis is to quantify uncertain or random events to support improved planning or decisionmaking. Risk analysis itself is a process of seeking to better understand and describe this uncertainty using the tools of probabilistic analysis and statistics. However, estimates of risk produced using these tools are themselves uncertain, so a distinction should be made between the different types of uncertainty present in any risk analysis. First, the “randomness of nature” that risk analysis directly seeks to quantify—in this instance, uncertainty regarding how frequently different areas of the coast can expect flood damage from storm...

  17. CHAPTER NINE Supporting Master Plan Development with CLARA
    (pp. 73-78)

    CLARA was built to flexibly evaluate flood risk reduction from a wide range of protection projects. CPRA identified a set of 34 structural protection projects to evaluate for the Master Plan, with the goal of identifying a high-performing combination of projects for implementation over the next 50 years. For detailed descriptions of the projects considered, please see Appendix A of the Master Plan (CPRA, 2012b). However, testing the effect of different combinations of projects in order to identify the best possible combination would require testing many thousands of possible combinations; including the 112 candidate nonstructural protection projects and 238 restoration...

  18. CHAPTER TEN Results from the Final Master Plan Analysis
    (pp. 79-112)

    CPRA developed a final version of Louisiana’s 2012 Master Plan in March 2012. Subsequent to finalizing the plan, CPRA asked the RAND team to evaluate the benefits of reducing flood damage from storm surge and waves to property and other physical assets in coastal Louisiana from the proposed coastwide projects. This chapter presents results from CLARA regarding potential changes in storm surge and flood damage over the 50-year span 2012–2061 with or without the 2012 Coastal Master Plan in place. In contrast to the initial analysis conducted to help compare and rank projects for inclusion in the plan (project-level...

  19. CHAPTER ELEVEN Conclusion
    (pp. 113-116)

    CLARA was designed to support the flexible exploration of a large set of risk reduction projects for coastal Louisiana across a range of scenarios representing uncertainty about future coastal conditions. Achieving this flexibility required some trade-offs with regard to model complexity and the size of data inputs. Its development and use as part of the Master Plan process illustrated the relative importance of different dimensions of uncertainty, produced new methods for estimating interior flood exceedances, and prompted many new questions for further inquiry. This chapter highlights some of the key insights drawn from CLARA, next steps for future research, and...

  20. Bibliography
    (pp. 117-118)