UNDERSTANDING THE FLOODING IN THE CITY: AN URBAN COMPOUND FLOODING MODEL USING MULTIPLE OPEN-SOURCED DYNAMIC DATASETS

Intense rainfall events or cloudbursts, and rising sea levels and tides are affecting millions of residents of New York City through catastrophic and nuisance floods. In response the City administration has enacted a series of mitigation programs involving, among other efforts, measuring the extent of the floods and rainfall in real time. This has resulted in the generation of multiple data sets available to the public that provide dynamic information about the city. We present here a first model that uses a number of these products from NYC Open Data in a compound and detailed flooding model of a small but representative section of the city: the campus of the College of Staten Island. Our aim is to use this as a sand box and starting point to further extend the model in complexity to include increasingly larger tracts within Staten Island, with the long-term goal of modeling the entirety of NYC, as a tool for data validation and impact-based forecasting. Our model currently involves a single input – a Mesonet weather station located on campus providing rainfall data – and the output of the model is compared to a single measurement of the discharge into the local creek. We consider other available information such as the presence of sub catchment basins in the watershed and different surface types.