Risk Analysis for Flood Mitigation on the Raritan (PAP014427)

Código

PAP014427

Autores

Qizhong Guo, Paul Kantor, Fred Roberts, David Robinson, Carlos A. Correa, Blake Cignarella

Tema

Flood risk management in mega cities

Resumo

We have developed a framework for flood mitigation risk analysis that applies generally to floods, and has applied it in this study of flood mitigation risk analysis for the Raritan Basin in New Jersey, USA. The framework we have developed involves a conceptual model of the relation among meteorological activity, hydrological models, infrastructure intervention, fine-grained topography, and economic impact. We have developed a hydrological model of the Raritan Basin. This model takes historical rainfall data, and has been calibrated to describe the behavior of one selected river gage during a significant 2007 flooding event. We have chosen one example of a mitigation strategy as a case in point to explore and develop the methodology, specifically Green Infrastructure. We used the calibrated model to compute the reduction in stream gage height (water level) over time as a result of implementing sufficient Green Infrastructure to reduce runoff depth by 1 inch (2.54 cm) throughout a relevant Watershed Management Area. In the econometric effort, we have developed a non-linear, threshold-based model that relates the cumulated or integrated amount of river activity above flood level to the FEMA insurance payouts, using historical data on both. This model was tested for four communities, and it achieves excellent predictive behavior against historical data, and can be used to relate the hydrological model results directly to FEMA payout records. Many possible explanatory variables were considered, and the most effective was found to be the aggregated quantity of water above flood level during the time directly associated to the flooding event that caused the claims and payouts. When these two streams of research are combined, the first is used to compute the effect of Green Infrastructure on the flow of water associated with an event. The second is used to calculate the corresponding decrease in total FEMA payouts. We applied this to one community, Manville, using rainfall data for a significant storm event that hit the region in 2007 to estimate runoff. Based on our models, the estimated cost savings due to the one inch (2.54 cm) reduction in runoff depth from Green Infrastructure in the region affecting the Manville Gage Station is about 6.1 million US dollars for a 68% reduction in FEMA payouts, which are estimated at 8.9 US million dollars without the mitigation. Our effort has demonstrated that linking of meteorology, hydrology, non-linear econometric modeling and sophisticated elicitation can provide a very powerful tool for informing and guiding discussion among all stakeholders. The present study, yielding non-linear models for four towns and hydrological models linked to one of these provides a proof of principle, a basis for estimating the costs of extending the model to the entire basin, and a roadmap for doing model-based and data-based risk analyses.