A flood preparedness tool for Chicago: Weather Research and Forecasting (WRF) model downscaling to improve rainfall forecasts and flood mitigation
Ragauskis, Michael Thomas
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https://hdl.handle.net/2142/115785
Description
Title
A flood preparedness tool for Chicago: Weather Research and Forecasting (WRF) model downscaling to improve rainfall forecasts and flood mitigation
Author(s)
Ragauskis, Michael Thomas
Issue Date
2022-04-27
Director of Research (if dissertation) or Advisor (if thesis)
Dominguez, Francina
Committee Member(s)
Jewett, Brian
Frame, Jeffrey
Department of Study
Atmospheric Sciences
Discipline
Atmospheric Sciences
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
numerical weather prediction
flooding
Chicago
rainfall
WRF
Abstract
Flooding is a chronic problem for the city of Chicago, Illinois, with only coastal areas of hurricane-ravaged states receiving more federal flood aid in some years. Low-income households and neighborhoods are especially hard hit. Exacerbating the problem is the lack of a system to provide accurate and timely forecasts of urban flooding to communities and hydrologic and hydraulic (H&H) infrastructure managers. This work is part of a large effort to build a tool to forecast and communicate flood risk at the community-scale for the city of Chicago. Using Weather Research and Forecasting (WRF) model downscaling to hindcast four significant flooding events, we demonstrate that areal rainfall forecasts can be generated at 1 km horizontal grid spacing and up to 24-hour lead times with more skill than current operational models. WRF generated precipitation can then force H&H models to provide sewer flow forecasts. These optimized forecasts will enable vulnerable communities and city-wide infrastructure managers to effectively prepare for and mitigate urban flooding and its effects on the Chicago-area waterway system.
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