[Presentation at Air Worldwide San Franciso office on Apr 12, 2013]
The level of damage of flood events does not solely depend on exposure to flood waters. Vulnerabilities due to various socio-economic factors such as population at risk, public awareness, and the presence of early warning systems, etc. should also be taken into account. Federal and state agencies, watershed management coalitions, insurance companies, need reliable decision support system to evaluate flood risk, to plan and design flood damage assessment and mitigation systems. In current practice, flood damage evaluations are generally carried out based on results obtained from one-dimensional (1D) numerical simulations. In some cases, however, 1D simulation is not able to accurately capture the dynamics of the flood events. This presentation describes a decision support system, which is based on 2D flood simulation results. The 2D computational results are complemented with information from various resources, such as census block layer, detailed survey data, and remote sensing images, to estimate loss-of-life and direct damages (meso or micro scale) to property under uncertainty. Flood damage calculations consider damages to residential, commercial and industrial buildings in urban areas, and damages to crops in rural areas. The decision support system takes advantage of fast raster layer operations in aGIS platform to generate flood hazard maps based on various user-defined criteria. Monte Carlo method based on an event tree analysis is introduced to account for uncertainties in various parameters. Case studies illustrate the uses of the proposed decision support system. The results show that the proposed decision support system allows stakeholders to have a better appreciation of the consequences of the flood. It can also be used for planning, design and evaluation of future flood mitigation measures.
The level of damage of flood events does not solely depend on exposure to flood waters. Vulnerabilities due to various socio-economic factors such as population at risk, public awareness, and the presence of early warning systems, etc. should also be taken into account. Federal and state agencies, watershed management coalitions, insurance companies, need reliable decision support system to evaluate flood risk, to plan and design flood damage assessment and mitigation systems. In current practice, flood damage evaluations are generally carried out based on results obtained from one-dimensional (1D) numerical simulations. In some cases, however, 1D simulation is not able to accurately capture the dynamics of the flood events. This presentation describes a decision support system, which is based on 2D flood simulation results. The 2D computational results are complemented with information from various resources, such as census block layer, detailed survey data, and remote sensing images, to estimate loss-of-life and direct damages (meso or micro scale) to property under uncertainty. Flood damage calculations consider damages to residential, commercial and industrial buildings in urban areas, and damages to crops in rural areas. The decision support system takes advantage of fast raster layer operations in a
