Improving upon Flash Flooding Forecasts for Two Major Great Lakes Cities

Flash flood vulnerability of large communities such as Chicago and Milwaukee is dependent on the resiliency of critical infrastructures, municipalities, the public and their homes to flash flood events. The magnitude of flash flood events is dependent on the identification of situations that lead to the most impactful flash flooding. This may include, but is not limited to: antecedent conditions such as recent precipitation events, soil moisture, and temperature; land use/land cover; the slope of the land (topography); and the identification of and sufficient forecast lead time of rainfall events likely to produce a flood event. This project developed unique approaches to flood vulnerability forecasting and risk monitoring through the use of ensemble model development and artificial intelligence probabilistic modeling. These resources can be utilized by National Weather Service (NWS) forecast offices and trained weather specialists in conjunction with other flash flood forecast models to monitor and assess the timing, location, and potential risk of flash flood occurrence. This presentation will review the general methodologies and output of the operational climatological risk monitoring and forecasts that were developed for the Chicago and Milwaukee forecast regions.