Quantifying Extreme Rainfall Events and Hydrologic Modeling for Flood-Resilient Bridge Design in Kano, Nigeria

Abstract

Climate change and some of its impacts (irregular rainfall and flooding) negatively affect hydraulic structures, especially in regions at risk of extreme weather conditions. Thus, it is critical to incorporate robust weather data in the design of hydraulic structures such as bridges. Therefore, this study evaluated extreme rainfall events and their implications for hydrologic and hydraulic modeling at a proposed bridge site in Kano, Nigeria. Analysis of 2001–2019 rainfall data revealed annual maximum rainfall ranging from 44.43 mm to 114.89 mm, with a mean of 82.67 mm and a standard deviation of 19.22 mm, exhibiting a positively skewed distribution. Frequency analysis using Hazen plotting positions estimated the largest observed storm (114.90 mm) to have a 19-year return period, with projected rainfall intensities reaching 135.45 mm, 174.83 mm and 212.67 mm for 50, 100 and 500-year return periods, respectively. Goodness-of-fit (GOF) tests identified the log-normal distribution as the best fit for estimating design storms. Intensity-Duration-Frequency (IDF) analysis disaggregated 24-hour rainfall into durations as short as 10 minutes, yielding peak intensities of 67.89 mm/hr for 2-year events and 221.34 mm/hr for 1000-year events. Hydrologic modeling incorporating catchment characteristics such as curve numbers, slopes, and basin areas simulated peak discharges of 78.34 m³/s, 142.67 m³/s and 186.45 m³/s for 2-year, 50-year and 100-year events, respectively at the proposed bridge location. The findings underscore the importance of robust rainfall modeling and hydrologic analysis in designing flood-resilient infrastructure, especially in regions susceptible to extreme weather events.