Modeling Rainfall Intensity-Duration-Frequency (IDF) and Establishing Climate Change Existence in Uyo-Nigeria Using Non-Stationary Approach — Oak Academic Publishing
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Modeling Rainfall Intensity-Duration-Frequency (IDF) and Establishing Climate Change Existence in Uyo-Nigeria Using Non-Stationary Approach
Department of Civil and Environmental Engineering, University of Port Harcourt, Port Harcourt, Nigeria
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Department of Civil and Environmental Engineering, University of Port Harcourt, Port Harcourt, Nigeria
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Department of Civil and Environmental Engineering, University of Port Harcourt, Port Harcourt, Nigeria
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Center for Occupational Health, Safety & Environment, University of Port Harcourt, Port Harcourt, Nigeria
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Department of Civil and Environmental Engineering, University of Port Harcourt, Port Harcourt, Nigeria
1 Department of Civil and Environmental Engineering, University of Port Harcourt, Port Harcourt, Nigeria
2 Department of Civil and Environmental Engineering, University of Port Harcourt, Port Harcourt, Nigeria
3 Department of Civil and Environmental Engineering, University of Port Harcourt, Port Harcourt, Nigeria
4 Center for Occupational Health, Safety & Environment, University of Port Harcourt, Port Harcourt, Nigeria
5 Department of Civil and Environmental Engineering, University of Port Harcourt, Port Harcourt, Nigeria
This study aims at establishing if climate change exists in the Niger Delta environment using non-stationary rainfall Intensity-Duration-Frequency (IDF) modelling incorporating time-variant parameters. To compute the intensity levels, the open-access R-studio software was used based on the General Extreme Value (GEV) distribution function. Among the four linear parameter models adopted for integrating time as a covariate, the fourth linear model incorporating scale and location with the shape function constant produced the least corrected Akaike Information Criteria (AICc), varying between 306.191 to 101.497 for 15 and 1440 minutes, respectively, selected for calibration of the GEV distribution equation. The non-stationary intensities yielded higher values above those of stationary models, proving that the assumption of stationary IDF models underestimated extreme events. The difference of 13.71 mm/hr (22.71%) to 14.26 mm/hr (17.0%) intensities implies an underestimation of the peak flood from a stationary IDF curve. The statistical difference at a 95% confidence level between stationary and non-stationary models was significant, confirming evidence of climatic change influenced by time-variant parameters. Consequently, emphasis should be on applying shorter-duration storms for design purposes occurring with higher intensities to help reduce the flood risk and resultant infrastructural failures.
KeywordsPrecipitationAnnual Maximum SeriesStationaryNon-StationaryIntensity-Duration-Frequency ModelsTrends
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