Quantitative Flood Resiliency and Vulnerability Model

Rouzbeh Nazari (Inventor), Mohamad Hosein Motamedi (Inventor)

    Research output: Innnovationinnovation

    Abstract

    <p class="Normal "><span style="font-family: 'Times New Roman';font-style: Normal;font-weight: bold;font-size: 16px;">Technology</span></p><p class="Normal "><span style="font-family: 'Times New Roman';font-style: Normal;font-size: 16px;">Flooding is the costliest and most common of the natural disasters that impact the United States. From 1980 to 2013, flooding was responsible for more than $260 billion in damage. Federal flood insurance claims have averaged approximately $2 billion annually in recent years with 2016 alone resulting in $4 billion in flood insurance losses in the National Flood Insurance Program. Due to the significant impacts of flooding in the United States there is a need for improved methods of modeling potential flood disasters for preparation, mitigation, response, and recovery. Researchers at Rowan University have developed a novel approach to measure resilience of buildings and infrastructures against flooding. The approach is a databased driven method for quantification of flood resilience of a given structure type for different hurricane categories. The assessment is based on dimensionless analytical functions related to the variation of functionality during a period of interest, including the losses in the disaster and the recovery path. The modeling tool accounts for flood characteristics, the features of individual structures including building height, construction material type, age of building, foundation type, and general building configuration. The modeling tool has been utilized by the New Jersey Department of Community Affairs for two towns greatly affected by Super Storm Sandy, the Brick and Woodbridge Townships.</span></p><p class="Normal "><span style="font-family: 'Times New Roman';font-style: Normal;font-size: 16px;">&nbsp;</span></p><p class="Normal "><span style="font-family: 'Times New Roman';font-style: Normal;font-weight: bold;font-size: 16px;">Competitive Advantages</span></p><ul style="list-style-type:disc"><li value="1" class="Normal " style="font-family: 'Verdana';font-style: Normal;font-weight: normal;font-size: 16px;color: #000000;"><span style="font-family: 'Times New Roman';font-style: Normal;font-size: 16px;">Enables assessment of the impact of different adaptation strategies on both individual structures and an entire community in a geographical information systems environment</span></li><li value="2" class="Normal " style="margin-right: 0px;font-family: 'Verdana';font-style: Normal;font-weight: normal;font-size: 16px;color: #000000;"><span style="font-family: 'Times New Roman';font-style: Normal;font-size: 16px;">Provides an accurate visualization in high-resolution damage and vulnerability assessment of large-scale communities impacted by flooding</span></li><li value="3" class="Normal " style="margin-right: 0px;font-family: 'Verdana';font-style: Normal;font-weight: normal;font-size: 16px;color: #000000;"><span style="font-family: 'Times New Roman';font-style: Normal;font-size: 16px;">Incorporates socioeconomic data along with hydrodynamic simulations to provide a true assessment of vulnerability and resilience</span></li><li value="4" class="Normal " style="margin-right: 0px;font-family: 'Verdana';font-style: Normal;font-weight: normal;font-size: 16px;color: #000000;"><span style="font-family: 'Times New Roman';font-style: Normal;font-size: 16px;">Expected to have higher accuracy and predictability across various flooding scenarios when compared to other flood mapping solutions</span></li></ul><p class="Normal "><span style="font-family: 'Times New Roman';font-style: Normal;font-weight: bold;font-size: 16px;">&nbsp;</span></p><p class="Normal "><span style="font-family: 'Times New Roman';font-style: Normal;font-weight: bold;font-size: 16px;">Opportunity</span></p><p class="Normal "><span style="font-family: 'Times New Roman';font-style: Normal;font-size: 16px;">The market opportunity is attractive for the quantitative flood resiliency model. The model can be integrated with geographical information systems or digital maps. The geographical information systems market is expected to increase to over $10 billion by 2023 and the digital maps market is expected to increase to over $20 billion by 2023. Rowan University is looking for a partner for further development and commercialization of this technology through a license. The inventor is available to collaborate with interested companies.</span></p>
    Original languageEnglish (US)
    StatePublished - Oct 2018

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