MODELLING ANNUAL MAXIMUM FLOOD OF RIVER KADUNA
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- Recommended for : Student Researchers
- NGN 3000
ABSTRACT
Records of flooding are increasing due to heavy storm which tend to filled most of the water bodies, thereby overflowing onto the land, causing damages and endangering the lives people. Flood also occur due to other factors such dam break, overflowing rivers etc. Most of this event occur with inadequate capacity of reservoirs, channels, drainages etc to store or convey the water appropriately Sediments transport due to heavy rain also contributed so much in reducing the capacity of most of the water bodies. Hence, water bodies tend to experience siltation as a result of this flood. By considering effect of flood, studies must be carried out to determine its magnitude for proper flood design. The study intended to employ the concept of frequency-based flood as one of the common methods of flood design. This method aimed at estimating the annual maximum flood of adequate length within a case study. Several methods of parameter estimate for flood frequency analysis evolves and determination of frequency factor of various distributions helps a lot to fit in the probability of exceedance into the distribution model through the statistical parameter of the distribution. The probability of exceedance gives the recurrence interval of flood. The magnitude of this flood must be studied as well as knowing the reliable probability distribution and plotting position to be used. Employing the principle of flood frequency analysis will be of help for determination of such magnitude. This study went by using secondary discharge data which was gotten form National Water Resources Institute, Kaduna. The data was utilized by MATLAB software. For the purpose of this research, 30years streamflow data was used of Kaduna State Water Works Gauging Station using MATLAB Software for the statistical and programming analysis. Four probability distributions were matched using eight various number of plotting positions which result or determine predicted discharges at various probability of exceedance. The statistical measurement was based on the concept of Goodness of Fit (GOF) in which Coefficient of determination (R-Square) and Root mean square error (RMSE). In the end, it was found that the best suitable plotting position for the catchment was determined to be Modified California, having the highest Adjusted R-square as 0.9604, 0.9622, 0.9728 and 0.9584 as well as validated RMSE value as 128.79, 175.39, 107.04 and 130.56 for normal, lognormal, pearson type III and log-pearson type III respectively. Furthermore, the best distribution that suit the catchment was discovered to be Pearson type III with Adjusted R-square and Validated RMSE value of 0.9728 and 107.04 respectively. Finally, the magnitude of the flood at different recurrence interval of 25, 50 and 100 years were vii determined to be 2838.60, 2936 and 2970.70 m3 /sec using the exponential model of Pearson Type III distribution.
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