Extreme Rainfall Estimates and Hydroclimatic Models for Improved Flood Forecasting

Authors: Damilola Eyelade*, University of California
Topics: Hazards and Vulnerability, Water Resources and Hydrology, Environmental Science
Keywords: rainfall extremes, hazards, decision support, data modeling
Session Type: Virtual Paper
Day: 4/8/2021
Start / End Time: 11:10 AM / 12:25 PM
Room: Virtual 7
Presentation File: No File Uploaded

Certain parts of the tropics are at risk of floods due to intense rainfall events which occur periodically. Increasing urbanization in such areas has led to an increase in flood impacts over time. With increasing urbanization, developing world cities, largely concentrated in the tropics, need to be able to predict and mitigate the hydrologic effects of extreme rainfall. Using the Ibadan metropolitan area of Nigeria as a case study, ground station data was integrated with satellite rainfall data to improve the modelling of extreme rainfall and hydrologic impacts. This involved determining the ratio of rainfall for each day between the ground station and the satellite data. The ratio was then adjusted using a distance weighting that reduces the effect of the ratio as distance increases. This adjusted ratio was then used to calculate rainfall for each grid cell. The non-adjusted and enhanced satellite data then served as meteorological inputs for rainfall - runoff models. A statistical analysis of extreme values for the non-adjusted and enhanced satellite input scenarios established the impact of the most extreme events on inundation extents. The techniques developed can inform risk modelling during urban development planning particularly where there is a need for bias correcting existing input satellite rainfall data for use in hydroclimatic models .

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