Jordan R. Fischbach

Estimating Surge-Based Flood Risk with the Coastal Louisiana Risk Assessment Model

ABSTRACT Johnson, D.R.; Fischbach, J.R., and Ortiz, D.S., 2013. Estimating surge-based flood risk with the coastal Louisiana risk assessment model. The Coastal Louisiana Risk Assessment model (CLARA) was designed to facilitate comparisons of current and future flood risk under a variety of protection system configurations in a wide range of environmental, operational, and economic uncertainties. It builds on previous studies of coastal risk by incorporating system fragility and a larger number of future scenarios than previously analyzed. Flood depths and direct economic damage from a wide range of simulated storm events are aggregated to produce a statistical summary of coastal risk under different assumptions about future conditions. CLARAs estimates of project-level effects on flood risk reduction were used as one of the key decision drivers in selecting the risk reduction projects included in the Master Plan. Depending on the scenario, the final alternative is projected to reduce expected annual damage by approximately 60 to 80% during the next 50 years relative to a future without action and, at the same time, balance other decision criteria.

Analysis to Support Louisiana's Flood Risk and Resilience Program and Application to the National Disaster Resilience Competition

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Computational Modeling of the Jamaica Bay System

1 billion available to states that have recently experienced a presidentially declared major disaster. Successful state applicants will be able to use these funds for recovery and other efforts to improve their resilience to future disasters. On October 27, 2015, the State of Louisiana submitted an application that proposes to use provided funds to elevate residential structures in Plaquemines, Lafourche, and Terrebonne parishes to reduce the risk of future flooding from storm surge. The State of Louisiana asked RAND to help develop this proposal by performing a quantitative analysis of the baseline flood risks and different allocations of funds for mitigation across the three parishes. RAND used a flood risk model and data developed for Louisianas 2017 Coastal Master Plan to perform an analysis and create a decision support tool to help the State evaluate flood risks and the effects of different nonstructural mitigation projects. The intended audience for this work includes policymakers working for the State of Louisiana and other interested parties. The work builds off prior RAND studies helping the State of Louisiana mitigate flood risk including Fischbach et al. The research reported here was conducted in the RAND Infrastructure Resilience and Environmental Policy program, which performs analyses on urbanization and other stresses. This includes research on infrastructure development, infrastructure financing, energy policy, urban planning and the role of public–private partnerships, transportation policy, climate response, mitigation and adaptation, environmental sustainability, and water resources management and coastal protection. Program research is supported by government agencies, foundations, and the private sector. This program is part of RAND Justice, Infrastructure and Environment, a division …

Coastal Louisiana Risk Assessment Model

Computational models are essential tools to support resilience planning for Jamaica Bay, or indeed anywhere (Hawes and Reed, 2006; Pickett et al., 2004; Walker et al., 2002; Gallopin, 2002). Models are simplifications of reality, constructed to highlight the interactions among physical, ecological, and social components of a system. Models connect observations with hypotheses and theories about how physical and social systems work, allowing scientists to articulate and test system understanding against data. Although there are physical and conceptual models, in the early twenty-first century, most models are deployed on computers and are increasingly used in distributed computing environments accessible through the Internet.