A flood preparedness tool for Chicago: Weather Research and Forecasting (WRF) model downscaling to improve rainfall forecasts and flood mitigation

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.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Atmospheric Sciences

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2022

Author dc:creator

• Ragauskis, Michael Thomas

Contributors dc:contributor

• Dominguez, Francina
• Jewett, Brian
• Frame, Jeffrey

• numerical weather prediction
• flooding
• Chicago
• rainfall
• WRF

Statement dc:rights

• Copyright 2022 Michael Ragauskis

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/115785

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F115785