ABSTRACT

Inadequate meteorological data for accurate designing, operation and planning of water resources against extreme rainfall event is a major challenge confronting engineers. Thirty two (32) years (1983-2014) daily rainfall data were collected for Port Harcourt, Calabar, Umuahia, Owerri, Benin, Warri, Enugu, Onitsha, Ibadan and Lagos from Nigeria Meteorological Agency (NIMET), Oshodi,   Lagos State for the study. The method of annual maximum series was used to select data sets for rainfall analysis.  Rainfall anomaly index and trend lines were plotted for each location to study the pattern of rainfall. Gumbel and Log Pearson Type 111 distributions were used to compute the observed rainfall intensity values at durations of 10, 15, 20, 30, 60,120,180,240, 300 and 360 minutes for return periods of 2, 5, 10,20,50 and 100 years. To obtain parameters for the IDF models for each location, the computed rainfall intensities were subjected to non-linear regression analysis using Microsoft Excel Optimization Technique Solver wizard for the respective durations and return periods. From the standardized anomaly index graphs, Calabar, Owerri, Warri, Onitsha, Benin, Enugu, Lagos, Ibadan, Port Harcourt and Umuahia had the highest positive rainfall anomaly index above average in the years 2010, 1996, 2008, 1995, 2011, 1997, 1988, 2014, 2006 and 1997, respectively, while their lowest negative rainfall anomaly index below average were in the years 1996, 1983, 1987, 1983, 2005, 2000,2008,1983,1983 and 1983, respectively. It is quite evident from the results, that the year 1983 had minimum amount of rainfall in most study stations. The trend analysis result showed that there is fluctuating rainfall pattern across the observed years. Though, each station had different trend. Port Harcourt had an annual rainfall trend that indicated a relatively steady increase. Owerri and Umuahia trend movement showed a decrease in annual rainfall and Lagos trend showed a relative steady decrease. All other stations showed a trend movement of annual rainfall increase. The inter-annual rainfall variability in all the study areas is due to climatic change. The IDF Models developed are for Enugu
𝐼=The performance of the models were analyzed by determining the chi-square(χ² ), coefficient of determination(R² ) and Root Mean Square Error(RMSE) of the fitted distributions. From the analysis, the R² values ranged from 0.76-1.00 and the RMSE from 0.04-15.92 for the Gumbel distribution for the studied locations. Also for the Log Pearson Type 111 distribution, R² values ranged from 0.98-1.00 with RMSE of 0.01-15.33 for the studied locations.  Log Pearson Type 111 distribution ranked first with respect to R² and RMSE for the IDF models, but no significant difference amongst the predicted intensities of the various IDF models.   Log Pearson Type 111 Model is recommended for the prediction of rainfall intensities for the studied locations. The Intensity Duration Frequency (IDF) Models (results) developed will serve as tools for the Engineers and Hydrologists in estimating storm water runoff from a watershed for the design of drainage systems, reservoir management and planning of water resources development.. This will mitigate flooding and its consequences. Also the findings when applied as demonstration tools in teaching land drainage courses to Engineering students, will enhance their understanding and appreciation of the course.